Restaurant / gen5
Viewer
!new Restaurant('restaurant5')
!restaurant5.name := 'Ocean Breeze'
!new Owner('owner10')
!owner10.name := 'Liam Cooper'
!owner10.percentageShares := 40
!insert (restaurant5, owner10) into RestaurantOwner
!new Owner('owner11')
!owner11.name := 'Sophia Turner'
!owner11.percentageShares := 60
!insert (restaurant5, owner11) into RestaurantOwner
!new Table('table11')
!table11.number := 11
!table11.description := 'Sunset view table'
!table11.capacity := 6
!new Table('table12')
!table12.number := 12
!table12.description := 'Upper deck'
!table12.capacity := 25
!new Table('table13')
!table13.number := 13
!table13.description := 'Garden table'
!table13.capacity := 10
!new RegularCustomer('customer6')
!customer6.name := 'Emma Watson'
!customer6.prefferedLanguage := #English
!new Waiter('waiter7')
!waiter7.name := 'Lucas White'
!waiter7.dateOfBirth := Date('1995-07-21')
!waiter7.phoneNumber := '555-2241'
!waiter7.spokenLanguage := #Spanish
!new HeadWaiter('headwaiter5')
!headwaiter5.name := 'Oliver Green'
!headwaiter5.dateOfBirth := Date('1983-02-19')
!headwaiter5.phoneNumber := '555-5561'
!insert (headwaiter5, waiter7) into HeadWaiterWaiter
!new Individual('reservation7')
!reservation7.time := Time('17:00')
!reservation7.date := Date('2023-11-14')
!reservation7.numberPeople := 5
!reservation7.name := 'Emma Watson'
!reservation7.phoneNumber := '555-7845'
!reservation7.number := 7
!reservation7.seating := #Patio
!reservation7.smoking := #NonSmoking
!insert (restaurant5, reservation7) into RestaurantReservation
!insert (reservation7, customer6) into ReservationCustomer
!insert (reservation7, waiter7) into ReservationWaiter
!insert (reservation7, table11) into ReservationTable
!new Banquet('reservation8')
!reservation8.time := Time('18:00')
!reservation8.date := Date('2024-01-01')
!reservation8.numberPeople := 35
!reservation8.name := 'Corporate Gala'
!reservation8.phoneNumber := '555-9054'
!reservation8.number := 8
!reservation8.groupName := 'Business Leaders'
!reservation8.paymentMethod := #Cash
!reservation8.busService := true
!insert (restaurant5, reservation8) into RestaurantReservation
!insert (reservation8, table12) into ReservationTable
!insert (reservation8, table13) into ReservationTable
!insert (reservation8, waiter7) into ReservationWaiter
!new BusDriver('busdriver4')
!busdriver4.name := 'Jack Taylor'
!busdriver4.dateOfBirth := Date('1970-04-30')
!busdriver4.phoneNumber := '555-3214'
!busdriver4.driverLicenseNr := 'DL159753'
!insert (reservation8, busdriver4) into BanquetBusDriver
!new ItemOrder('itemOrder5')
!itemOrder5.time := Time('17:30')
!insert (reservation7, itemOrder5) into ReservationItemOrdered
!new MenuItem('menuItem5')
!menuItem5.description := 'Grilled Lobster'
!menuItem5.prepTime := 35.0
!menuItem5.classification := #Main
!insert (itemOrder5, menuItem5) into ItemOrderMenuItem
!new FoodItem('foodItem5')
!foodItem5.number := 105
!foodItem5.description := 'Fresh Lobster'
!foodItem5.purchaseFlag := true
!foodItem5.unit := #Pound
!insert (menuItem5, foodItem5) into MenuItemFoodItem
!new Allergen('allergen5')
!allergen5.type := #Seafood
!insert (foodItem5, allergen5) into FoodItemAllergen
!new Cook('cook5')
!cook5.name := 'Sophia Reed'
!cook5.dateOfBirth := Date('1989-11-02')
!cook5.phoneNumber := '555-8877'
!cook5.yearsOfExperience := 8
!new Chef('chef5')
!chef5.name := 'Ethan King'
!chef5.dateOfBirth := Date('1986-03-05')
!chef5.phoneNumber := '555-6688'
!insert (menuItem5, chef5) into MenuItemChef
!insert (chef5, cook5) into ChefCook model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople Given a conceptual model expressed in the UML-based Specification Environment (USE), your task is to generate valid and realistic instances that conform to the provided model. <requirements> - Instances must be syntactically correct according to the USE syntax_reference. - Avoid unnecessary comments and output the instance in plain text (i.e., not markdown). - Make sure instances fulfill all the model's constraints, and that multiplicities, relationships, and attributes are valid and realistic. - Provide multiple instances with diverse data values and structure. </requirements> <syntax_reference> Here there is a snippet showing how to create objects and set values in the specific .soil language required: -- This is a comment example -- Primitive data types: -- Integer i.e. 1, 2, 3, etc. -- Real i.e. 1.0, 21.89, 322.05556, etc. -- Boolean i.e. true or false -- String i.e. 'Hello World' -- You can create instances with the following syntax: !new <instance type>('<instance name>') -- Example: !new Client('client1') !new Store('store4') -- You can assign values to attributes for a created instance with the following syntax: !<instance name>.<attribute name> := <value> -- Example for different data types: !client1.clientId := 1 -- For Integer !client1.balance := 1123.45 -- For Real !client1.name := 'John' -- For Strings !store4.available := true -- For Boolean -- You can create associations between instances with the following syntax: !insert (<instance name1>, <instance name2>) into <association name> -- Example: !insert (client1, store4) into ClientStore -- Custom data types usage: -- dataType Location -- operations -- Location(x : Real, y : Real) -- some other operations -- end -- You can create custom data types by calling the constructor directly; in this case, the constructor of Location requires two arguments: x and y of type Real. So it can be used as follows: !store4.location := Location(14.0, 289.0) -- Enums usage: -- enum Type { Clothes, Shoes } -- Can be used as follows: !store4.type := #Clothes </syntax_reference> Please generate another instance that is structurally and semantically different from the previous ones. The last output is partially incorrect:
checking invariants...
checking invariant (1) `Cook::PositiveExperience': OK.
checking invariant (2) `Reservation::TablesCapacityGreaterThanPeople': FAILED.
-> false : Boolean
checking invariant (3) `Restaurant::TotalOwnerShares': OK.
checking invariant (4) `Table::PositiveCapacity': OK.
checked 4 invariants in 0.001s, 1 failure.
Please provide the complete output corrected The last output is partially incorrect:
checking invariants...
checking invariant (1) `Cook::PositiveExperience': OK.
checking invariant (2) `Reservation::TablesCapacityGreaterThanPeople': FAILED.
-> false : Boolean
checking invariant (3) `Restaurant::TotalOwnerShares': OK.
checking invariant (4) `Table::PositiveCapacity': OK.
checked 4 invariants in 0.001s, 1 failure.
Please provide the complete output corrected <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant5')
!restaurant5.name := 'Ocean Breeze'
!new Owner('owner10')
!owner10.name := 'Liam Cooper'
!owner10.percentageShares := 40
!insert (restaurant5, owner10) into RestaurantOwner
!new Owner('owner11')
!owner11.name := 'Sophia Turner'
!owner11.percentageShares := 60
!insert (restaurant5, owner11) into RestaurantOwner
!new Table('table11')
!table11.number := 11
!table11.description := 'Sunset view table'
!table11.capacity := 6
!new Table('table12')
!table12.number := 12
!table12.description := 'Upper deck'
!table12.capacity := 25
!new Table('table13')
!table13.number := 13
!table13.description := 'Garden table'
!table13.capacity := 10
!new RegularCustomer('customer6')
!customer6.name := 'Emma Watson'
!customer6.prefferedLanguage := #English
!new Waiter('waiter7')
!waiter7.name := 'Lucas White'
!waiter7.dateOfBirth := Date('1995-07-21')
!waiter7.phoneNumber := '555-2241'
!waiter7.spokenLanguage := #Spanish
!new HeadWaiter('headwaiter5')
!headwaiter5.name := 'Oliver Green'
!headwaiter5.dateOfBirth := Date('1983-02-19')
!headwaiter5.phoneNumber := '555-5561'
!insert (headwaiter5, waiter7) into HeadWaiterWaiter
!new Individual('reservation7')
!reservation7.time := Time('17:00')
!reservation7.date := Date('2023-11-14')
!reservation7.numberPeople := 5
!reservation7.name := 'Emma Watson'
!reservation7.phoneNumber := '555-7845'
!reservation7.number := 7
!reservation7.seating := #Patio
!reservation7.smoking := #NonSmoking
!insert (restaurant5, reservation7) into RestaurantReservation
!insert (reservation7, customer6) into ReservationCustomer
!insert (reservation7, waiter7) into ReservationWaiter
!insert (reservation7, table11) into ReservationTable
!new Banquet('reservation8')
!reservation8.time := Time('18:00')
!reservation8.date := Date('2024-01-01')
!reservation8.numberPeople := 35
!reservation8.name := 'Corporate Gala'
!reservation8.phoneNumber := '555-9054'
!reservation8.number := 8
!reservation8.groupName := 'Business Leaders'
!reservation8.paymentMethod := #Cash
!reservation8.busService := true
!insert (restaurant5, reservation8) into RestaurantReservation
!insert (reservation8, table12) into ReservationTable
!insert (reservation8, table13) into ReservationTable
!insert (reservation8, waiter7) into ReservationWaiter
!new BusDriver('busdriver4')
!busdriver4.name := 'Jack Taylor'
!busdriver4.dateOfBirth := Date('1970-04-30')
!busdriver4.phoneNumber := '555-3214'
!busdriver4.driverLicenseNr := 'DL159753'
!insert (reservation8, busdriver4) into BanquetBusDriver
!new ItemOrder('itemOrder5')
!itemOrder5.time := Time('17:30')
!insert (reservation7, itemOrder5) into ReservationItemOrdered
!new MenuItem('menuItem5')
!menuItem5.description := 'Grilled Lobster'
!menuItem5.prepTime := 35.0
!menuItem5.classification := #Main
!insert (itemOrder5, menuItem5) into ItemOrderMenuItem
!new FoodItem('foodItem5')
!foodItem5.number := 105
!foodItem5.description := 'Fresh Lobster'
!foodItem5.purchaseFlag := true
!foodItem5.unit := #Pound
!insert (menuItem5, foodItem5) into MenuItemFoodItem
!new Allergen('allergen5')
!allergen5.type := #Seafood
!insert (foodItem5, allergen5) into FoodItemAllergen
!new Cook('cook5')
!cook5.name := 'Sophia Reed'
!cook5.dateOfBirth := Date('1989-11-02')
!cook5.phoneNumber := '555-8877'
!cook5.yearsOfExperience := 8
!new Chef('chef5')
!chef5.name := 'Ethan King'
!chef5.dateOfBirth := Date('1986-03-05')
!chef5.phoneNumber := '555-6688'
!insert (menuItem5, chef5) into MenuItemChef
!insert (chef5, cook5) into ChefCook
</object_model> LLM as a Judge
The object model is logically consistent and faithfully represents a real-world restaurant scenario. The capacities match the reservation sizes (e.g., a 35-person banquet occupying two tables with a combined capacity of 35), owner shares add up to exactly 100%, and attributes such as prep time, allergens (Lobster containing Seafood), and dates of birth are all fully plausible.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.13 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/96 |
| Multiplicities | 0/18 |
| Invariants | 0/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 98.1% |
| String Equals | 99.7% |
| String LV | 88.3% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 78.9% |
| Attributes | 89.7% |
| Relationships | 100.0% |
Uncovered Items 10
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 18/∞ |
| Attributes | 60/60 |
| Relationships | 18/∞ |
Viewer
!new Restaurant('restaurant25')
!restaurant25.name := 'Lotus Blossom'
!new Owner('owner52')
!owner52.name := 'Somchai Chaiyaratana'
!owner52.percentageShares := 50
!new Owner('owner53')
!owner53.name := 'Naree Wong'
!owner53.percentageShares := 50
!insert (restaurant25, owner52) into RestaurantOwner
!insert (restaurant25, owner53) into RestaurantOwner
!new Table('table63')
!table63.number := 1
!table63.description := 'Intimate table overlooking the koi fish pond.'
!table63.capacity := 3
!new Table('table64')
!table64.number := 2
!table64.description := 'Traditional Thai seating with floor cushions.'
!table64.capacity := 4
!new Table('table65')
!table65.number := 3
!table65.description := 'Large family table in the central dining area.'
!table65.capacity := 12
!new RegularCustomer('customer20')
!customer20.name := 'Chompoo Kaew'
!customer20.prefferedLanguage := #English
!new RegularCustomer('customer21')
!customer21.name := 'David Johnson'
!customer21.prefferedLanguage := #English
!new Individual('individualReservation13')
!individualReservation13.date := Date('2024-02-14')
!individualReservation13.time := Time('17:45')
!individualReservation13.numberPeople := 1
!individualReservation13.name := 'Chompoo Kaew'
!individualReservation13.phoneNumber := '1234567890' -- Arbitrary phone number
!individualReservation13.seating := #Inside
!individualReservation13.smoking := #NonSmoking
!individualReservation13.number := 13
!insert (restaurant25, individualReservation13) into RestaurantReservation
!insert (individualReservation13, customer20) into ReservationCustomer
!insert (individualReservation13, table63) into ReservationTable
!new Banquet('banquet21')
!banquet21.date := Date('2024-02-14')
!banquet21.time := Time('20:30')
!banquet21.groupName := 'David Johnson\'s Team Dinner'
!banquet21.numberPeople := 14
!banquet21.paymentMethod := #CreditCard
!insert (restaurant25, banquet21) into RestaurantReservation
!insert (banquet21, customer21) into ReservationCustomer
!insert (banquet21, table65) into ReservationTable
!insert (banquet21, table64) into ReservationTable
!new Waiter('waiter46')
!waiter46.name := 'Pimchai Prajun'
!waiter46.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter46.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter46.spokenLanguage := #English
!new Waiter('waiter47')
!waiter47.name := 'Somchai Rattanakosin'
!waiter47.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter47.phoneNumber := '3456789012' -- Arbitrary phone number
!waiter47.spokenLanguage := #English
!insert (individualReservation13, waiter46) into ReservationWaiter
!insert (banquet21, waiter46) into ReservationWaiter
!insert (banquet21, waiter47) into ReservationWaiter
!new HeadWaiter('headwaiter20')
!headwaiter20.name := 'Jintana Preecha'
!headwaiter20.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter20.phoneNumber := '4567890123' -- Arbitrary phone number
!insert (headwaiter20, waiter46) into HeadWaiterWaiter
!insert (headwaiter20, waiter47) into HeadWaiterWaiter
!new BusDriver('busdriver21')
!busdriver21.name := 'Ananda Saetang'
!insert (banquet21, busdriver21) into BanquetBusDriver
!new Chef('chef27')
!chef27.name := 'Noi Srisuphan'
!chef27.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef27.phoneNumber := '5678901234' -- Arbitrary phone number
!new Cook('cook32')
!cook32.name := 'Kanchana Sutham'
!cook32.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook32.phoneNumber := '6789012345' -- Arbitrary phone number
!cook32.yearsOfExperience := 4
!insert (chef27, cook32) into ChefCook
!new MenuItem('menuitem36')
!menuitem36.description := 'Spicy and sour Thai soup with shrimp.'
!menuitem36.prepTime := 40.0
!menuitem36.classification := #Apetizer
!insert (menuitem36, chef27) into MenuItemChef
!new FoodItem('fooditem61')
!fooditem61.number := 61
!fooditem61.description := 'Shrimp'
!fooditem61.purchaseFlag := true
!fooditem61.unit := #Pound
!new FoodItem('fooditem62')
!fooditem62.number := 62
!fooditem62.description := 'Lemongrass'
!fooditem62.purchaseFlag := true
!fooditem62.unit := #Gram
!new FoodItem('fooditem63')
!fooditem63.number := 63
!fooditem63.description := 'Chili'
!fooditem63.purchaseFlag := true
!fooditem63.unit := #Gram
!insert (menuitem36, fooditem61) into MenuItemFoodItem
!insert (menuitem36, fooditem62) into MenuItemFoodItem
!insert (menuitem36, fooditem63) into MenuItemFoodItem
!new Allergen('allergen22')
!allergen22.type := #Seafood
!insert (fooditem61, allergen22) into FoodItemAllergen
!new MenuItem('menuitem37')
!menuitem37.description := 'Sweet sticky rice served with ripe mango slices.'
!menuitem37.prepTime := 20.0
!menuitem37.classification := #Dessert
!insert (menuitem37, chef27) into MenuItemChef
!new FoodItem('fooditem64')
!fooditem64.number := 64
!fooditem64.description := 'Glutinous Rice'
!fooditem64.purchaseFlag := true
!fooditem64.unit := #Gram
!new FoodItem('fooditem65')
!fooditem65.number := 65
!fooditem65.description := 'Mango'
!fooditem65.purchaseFlag := true
!fooditem65.unit := #Gram
!new FoodItem('fooditem66')
!fooditem66.number := 66
!fooditem66.description := 'Coconut Milk'
!fooditem66.purchaseFlag := true
!fooditem66.unit := #Ounce
!insert (menuitem37, fooditem64) into MenuItemFoodItem
!insert (menuitem37, fooditem65) into MenuItemFoodItem
!insert (menuitem37, fooditem66) into MenuItemFoodItem model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
### Restaurant Scenario
In the vibrant and bustling city of Bangkok, "Lotus Blossom" offers a culinary journey through traditional Thai flavors combined with modern fusion elements. This establishment is known for its warm hospitality and intricate dishes that capture the essence of Thai cuisine.
**Restaurant Instance:**
- **Name:** Lotus Blossom
**Owner Instances:**
- **Name:** Somchai Chaiyaratana
- **Shares:** 50%
- **Language:** Thai
- **Related Restaurant:** Lotus Blossom
- **Name:** Naree Wong
- **Shares:** 50%
- **Language:** Thai, English
- **Related Restaurant:** Lotus Blossom
**Table Instances:**
- **Table 1**
- **Number:** A5
- **Description:** Intimate table overlooking the koi fish pond.
- **Capacity:** 3
- **Table 2**
- **Number:** C7
- **Description:** Traditional Thai seating with floor cushions.
- **Capacity:** 4
- **Table 3**
- **Number:** G10
- **Description:** Large family table in the central dining area.
- **Capacity:** 12
**Regular Customer Instances:**
- **Name:** Chompoo Kaew
- **Preferred Language:** Thai
- **Reservation Type:** Individual Reservation
- Associated with Lotus Blossom
- **Name:** David Johnson
- **Preferred Language:** English
- **Reservation Type:** Banquet Reservation
- Associated with Lotus Blossom
**Reservation Instances:**
- **Individual Reservation for Chompoo Kaew**
- **Date:** 2024-02-14
- **Time:** 17:45
- **Seating Preference:** Inside
- **Smoking Preference:** NonSmoking
- **Assigned Table:** Table A5 (Capacity 3)
- **Associated Waiter:** Pimchai Prajun
- **Banquet Reservation for David Johnson's Team Dinner**
- **Date:** 2024-02-14
- **Time:** 20:30
- **Number of People:** 14
- **Payment Method:** CreditCard
- **Assigned Tables:** Table G10 (Capacity 12) and Table C7 (Capacity 4)
- **Bus Driver:** Ananda Saetang
- **Associated Waiters:** Pimchai Prajun and Somchai Rattanakosin
**Waiter Instances:**
- **Name:** Pimchai Prajun
- **Languages Spoken:** Thai, English
- **Experience:** 5 years
- Associated with Lotus Blossom and both Reservations
- **Name:** Somchai Rattanakosin
- **Languages Spoken:** Thai, Mandarin
- **Experience:** 3 years
- Associated with Lotus Blossom and Banquet Reservation
**Head Waiter Instance:**
- **Name:** Jintana Preecha
- **Languages Spoken:** Thai, French
- **Experience:** 11 years
- **Responsible for:** Pimchai Prajun and Somchai Rattanakosin
**Bus Driver Instance:**
- **Name:** Ananda Saetang
- **Experience:** 10 years
- Associated with David's Banquet
**Chef Instance:**
- **Name:** Noi Srisuphan
- **Languages Spoken:** Thai, English
- **Experience:** 18 years
- **Supervises Cooks:** Kanchana Sutham
**Cook Instance:**
- **Name:** Kanchana Sutham
- **Languages Spoken:** Thai
- **Experience:** 4 years
- Supervised by Noi Srisuphan
**MenuItem Instances:**
- **Tom Yum Goong**
- **Description:** Spicy and sour Thai soup with shrimp.
- **Preparation Time:** 40 minutes
- **Classification:** Apetizer
- **Designed by Chef:** Noi Srisuphan
- **Food Items Used:** Shrimp, Lemongrass, Chili
- **Mango Sticky Rice**
- **Description:** Sweet sticky rice served with ripe mango slices.
- **Preparation Time:** 20 minutes
- **Classification:** Dessert
- **Designed by Chef:** Noi Srisuphan
- **Food Items Used:** Glutinous Rice, Mango, Coconut Milk
**FoodItem Instances:**
- **Shrimp**
- **Unit:** Pound
- **Purchase:** True
- **Allergens:** Seafood
- **Lemongrass**
- **Unit:** Gram
- **Purchase:** True
- **Allergens:** None
- **Coconut Milk**
- **Unit:** Ounce
- **Purchase:** True
- **Allergens:** None
**Allergen Instances:**
- **Seafood**
- Associated with Food Item: Shrimp
This diverse instance captures the unique flavors and cultural aspects of "Lotus Blossom" in Bangkok, fulfilling all desired elements and constraints while offering a glimpse into the dynamic operations of a Thai fusion restaurant. The last output is partially incorrect:
temp.soil> !customer20.name := 'Chompoo Kaew'
temp.soil> !customer20.prefferedLanguage := #Thai
<input>:1:0: generation of expression `#Thai' failed, with following error:
<input>:1:33: Undefined enumeration literal `Thai'.
temp.soil> !waiter46.phoneNumber := '2345678901' -- Arbitrary phone number
temp.soil> !waiter46.spokenLanguage := #Thai
<input>:1:0: generation of expression `#Thai' failed, with following error:
<input>:1:28: Undefined enumeration literal `Thai'.
temp.soil> !waiter47.phoneNumber := '3456789012' -- Arbitrary phone number
temp.soil> !waiter47.spokenLanguage := #Thai
<input>:1:0: generation of expression `#Thai' failed, with following error:
<input>:1:28: Undefined enumeration literal `Thai'.
Please provide the complete output corrected <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant25')
!restaurant25.name := 'Lotus Blossom'
!new Owner('owner52')
!owner52.name := 'Somchai Chaiyaratana'
!owner52.percentageShares := 50
!new Owner('owner53')
!owner53.name := 'Naree Wong'
!owner53.percentageShares := 50
!insert (restaurant25, owner52) into RestaurantOwner
!insert (restaurant25, owner53) into RestaurantOwner
!new Table('table63')
!table63.number := 1
!table63.description := 'Intimate table overlooking the koi fish pond.'
!table63.capacity := 3
!new Table('table64')
!table64.number := 2
!table64.description := 'Traditional Thai seating with floor cushions.'
!table64.capacity := 4
!new Table('table65')
!table65.number := 3
!table65.description := 'Large family table in the central dining area.'
!table65.capacity := 12
!new RegularCustomer('customer20')
!customer20.name := 'Chompoo Kaew'
!customer20.prefferedLanguage := #English
!new RegularCustomer('customer21')
!customer21.name := 'David Johnson'
!customer21.prefferedLanguage := #English
!new Individual('individualReservation13')
!individualReservation13.date := Date('2024-02-14')
!individualReservation13.time := Time('17:45')
!individualReservation13.numberPeople := 1
!individualReservation13.name := 'Chompoo Kaew'
!individualReservation13.phoneNumber := '1234567890' -- Arbitrary phone number
!individualReservation13.seating := #Inside
!individualReservation13.smoking := #NonSmoking
!individualReservation13.number := 13
!insert (restaurant25, individualReservation13) into RestaurantReservation
!insert (individualReservation13, customer20) into ReservationCustomer
!insert (individualReservation13, table63) into ReservationTable
!new Banquet('banquet21')
!banquet21.date := Date('2024-02-14')
!banquet21.time := Time('20:30')
!banquet21.groupName := 'David Johnson\'s Team Dinner'
!banquet21.numberPeople := 14
!banquet21.paymentMethod := #CreditCard
!insert (restaurant25, banquet21) into RestaurantReservation
!insert (banquet21, customer21) into ReservationCustomer
!insert (banquet21, table65) into ReservationTable
!insert (banquet21, table64) into ReservationTable
!new Waiter('waiter46')
!waiter46.name := 'Pimchai Prajun'
!waiter46.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter46.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter46.spokenLanguage := #English
!new Waiter('waiter47')
!waiter47.name := 'Somchai Rattanakosin'
!waiter47.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter47.phoneNumber := '3456789012' -- Arbitrary phone number
!waiter47.spokenLanguage := #English
!insert (individualReservation13, waiter46) into ReservationWaiter
!insert (banquet21, waiter46) into ReservationWaiter
!insert (banquet21, waiter47) into ReservationWaiter
!new HeadWaiter('headwaiter20')
!headwaiter20.name := 'Jintana Preecha'
!headwaiter20.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter20.phoneNumber := '4567890123' -- Arbitrary phone number
!insert (headwaiter20, waiter46) into HeadWaiterWaiter
!insert (headwaiter20, waiter47) into HeadWaiterWaiter
!new BusDriver('busdriver21')
!busdriver21.name := 'Ananda Saetang'
!insert (banquet21, busdriver21) into BanquetBusDriver
!new Chef('chef27')
!chef27.name := 'Noi Srisuphan'
!chef27.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef27.phoneNumber := '5678901234' -- Arbitrary phone number
!new Cook('cook32')
!cook32.name := 'Kanchana Sutham'
!cook32.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook32.phoneNumber := '6789012345' -- Arbitrary phone number
!cook32.yearsOfExperience := 4
!insert (chef27, cook32) into ChefCook
!new MenuItem('menuitem36')
!menuitem36.description := 'Spicy and sour Thai soup with shrimp.'
!menuitem36.prepTime := 40.0
!menuitem36.classification := #Apetizer
!insert (menuitem36, chef27) into MenuItemChef
!new FoodItem('fooditem61')
!fooditem61.number := 61
!fooditem61.description := 'Shrimp'
!fooditem61.purchaseFlag := true
!fooditem61.unit := #Pound
!new FoodItem('fooditem62')
!fooditem62.number := 62
!fooditem62.description := 'Lemongrass'
!fooditem62.purchaseFlag := true
!fooditem62.unit := #Gram
!new FoodItem('fooditem63')
!fooditem63.number := 63
!fooditem63.description := 'Chili'
!fooditem63.purchaseFlag := true
!fooditem63.unit := #Gram
!insert (menuitem36, fooditem61) into MenuItemFoodItem
!insert (menuitem36, fooditem62) into MenuItemFoodItem
!insert (menuitem36, fooditem63) into MenuItemFoodItem
!new Allergen('allergen22')
!allergen22.type := #Seafood
!insert (fooditem61, allergen22) into FoodItemAllergen
!new MenuItem('menuitem37')
!menuitem37.description := 'Sweet sticky rice served with ripe mango slices.'
!menuitem37.prepTime := 20.0
!menuitem37.classification := #Dessert
!insert (menuitem37, chef27) into MenuItemChef
!new FoodItem('fooditem64')
!fooditem64.number := 64
!fooditem64.description := 'Glutinous Rice'
!fooditem64.purchaseFlag := true
!fooditem64.unit := #Gram
!new FoodItem('fooditem65')
!fooditem65.number := 65
!fooditem65.description := 'Mango'
!fooditem65.purchaseFlag := true
!fooditem65.unit := #Gram
!new FoodItem('fooditem66')
!fooditem66.number := 66
!fooditem66.description := 'Coconut Milk'
!fooditem66.purchaseFlag := true
!fooditem66.unit := #Ounce
!insert (menuitem37, fooditem64) into MenuItemFoodItem
!insert (menuitem37, fooditem65) into MenuItemFoodItem
!insert (menuitem37, fooditem66) into MenuItemFoodItem
</object_model> LLM as a Judge
The scenario logically and consistently represents a real-world Thai restaurant. The reservations respect table capacities, the ages of workers are physically possible, ingredient quantities use appropriate units of measure (e.g., Shrimp in Pounds, Spices in Grams), and the specified allergens accurately correspond to the correct food items (e.g., Seafood for Shrimp).
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.49 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/131 |
| Multiplicities | 0/25 |
| Invariants | 0/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 97.9% |
| String Equals | 99.8% |
| String LV | 89.2% |
| Shannon (Active) | 0.298 ± 0.426 |
| Shannon (All) | 0.173 ± 0.245 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 73.7% |
| Attributes | 75.9% |
| Relationships | 84.6% |
Uncovered Items 21
Show all 14 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 25/∞ |
| Attributes | 81/88 |
| Relationships | 25/∞ |
Viewer
!new Restaurant('restaurant24')
!restaurant24.name := 'Taste of Traditions'
!new Owner('owner50')
!owner50.name := 'Malik Sadiq'
!owner50.percentageShares := 33
!new Owner('owner51')
!owner51.name := 'Sofia Wang'
!owner51.percentageShares := 67
!insert (restaurant24, owner50) into RestaurantOwner
!insert (restaurant24, owner51) into RestaurantOwner
!new RegularCustomer('customer19')
!customer19.name := 'Lena Müller'
!customer19.prefferedLanguage := #German
!new HeadWaiter('headwaiter19')
!headwaiter19.name := 'Juan Carlos'
!headwaiter19.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!headwaiter19.phoneNumber := '1234567890' -- Arbitrary phone number
!new Waiter('waiter45')
!waiter45.name := 'Federica Rossi'
!waiter45.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!waiter45.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter45.spokenLanguage := #English
!insert (headwaiter19, waiter45) into HeadWaiterWaiter
!new Chef('chef26')
!chef26.name := 'Greta Nyman'
!chef26.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef26.phoneNumber := '3456789012' -- Arbitrary phone number
!new Cook('cook31')
!cook31.name := 'Vinod Sharma'
!cook31.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!cook31.phoneNumber := '4567890123' -- Arbitrary phone number
!cook31.yearsOfExperience := 7
!insert (chef26, cook31) into ChefCook
!new BusDriver('busdriver20')
!busdriver20.name := 'Joanne Lee'
!new Table('table61')
!table61.number := 15
!table61.description := 'Cozy corner booth'
!table61.capacity := 6
!new Table('table62')
!table62.number := 16
!table62.description := 'Community table'
!table62.capacity := 8
!new MenuItem('menuitem35')
!menuitem35.description := 'A rich and satisfying stew with seasonal vegetables.'
!menuitem35.prepTime := 35.0
!menuitem35.classification := #Main
!insert (menuitem35, chef26) into MenuItemChef
!new FoodItem('fooditem59')
!fooditem59.number := 59
!fooditem59.description := 'Beef Chunks'
!fooditem59.purchaseFlag := true
!fooditem59.unit := #Pound
!new FoodItem('fooditem60')
!fooditem60.number := 60
!fooditem60.description := 'Carrot'
!fooditem60.purchaseFlag := false
!fooditem60.unit := #Gram
!insert (menuitem35, fooditem59) into MenuItemFoodItem
!insert (menuitem35, fooditem60) into MenuItemFoodItem
!new Banquet('banquet20')
!banquet20.date := Date('2023-11-25')
!banquet20.time := Time('17:00')
!banquet20.groupName := 'Cultural Dinner Exchange'
!banquet20.numberPeople := 10
!banquet20.paymentMethod := #CreditCard
!insert (restaurant24, banquet20) into RestaurantReservation
!insert (banquet20, table61) into ReservationTable
!insert (banquet20, table62) into ReservationTable
!insert (banquet20, waiter45) into ReservationWaiter
!insert (banquet20, busdriver20) into BanquetBusDriver
!new ItemOrder('itemorder5')
!itemorder5.time := Time('17:20')
!insert (banquet20, itemorder5) into ReservationItemOrdered
!insert (itemorder5, menuitem35) into ItemOrderMenuItem model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Boundary Case Instance: Restaurant System
### Restaurant Details
- **Restaurant Name**: "Taste of Traditions"
### Owners
1. **Owner 1**:
- Name: Malik Sadiq
- Percentage Shares: 33%
2. **Owner 2**:
- Name: Sofia Wang
- Percentage Shares: 67%
### Regular Customers
- **Regular Customer**:
- Name: Lena Müller
- Preferred Language: German
### Workers
1. **Head Waiter**:
- Name: Juan Carlos
- Years of Experience: 4
- Languages Spoken: Spanish, English
2. **Waiters**:
- Name: Federica Rossi
- Years of Experience: 3
- Languages Spoken: Italian, English
- Head Waiter: Juan Carlos
3. **Chefs**:
- Name: Greta Nyman
- Years of Experience: 7
- Languages Spoken: Swedish, English
4. **Cooks**:
- Name: Vinod Sharma
- Years of Experience: 7
5. **Bus Driver**:
- Name: Joanne Lee
- Experience Years: 2
### Tables
1. **Table 1**:
- Number: 15
- Description: "Cozy corner booth"
- Capacity: 6
2. **Table 2**:
- Number: 16
- Description: "Community table"
- Capacity: 8
### Menu Items
1. **Menu Item**:
- Name: "Hearty Beef Stew"
- Description: "A rich and satisfying stew with seasonal vegetables."
- Preparation Time: 35 minutes
- Classifications: Main, Seasonal
- Designer: Greta Nyman
### Food Items
1. **Food Item**:
- Name: "Beef Chunks"
- Unit: Pound
- Purchase Flag: True
2. **Food Item**:
- Name: "Carrot"
- Unit: Gram
- Purchase Flag: False
### Allergens
- No allergens associated (minimum multiplicity).
### Reservations
1. **Reservation (Banquet)**:
- Reservation Date: "2023-11-25"
- Reservation Time: "17:00"
- Group Name: "Cultural Dinner Exchange"
- Payment Method: CreditCard
- Serving Waiter: Federica Rossi
- Bus Driver: Joanne Lee
- Assigned Tables: Table 1, Table 2
- Number of People: 10 (Spanning two tables for a community-oriented gathering)
### Item Orders
1. **Item Order 1**:
- Time Ordered: "17:20"
- Associated Reservation: Banquet Reservation for "Cultural Dinner Exchange"
- Ordered Menu Item: Hearty Beef Stew
### Relationships
- "Taste of Traditions" is jointly owned by Malik Sadiq and Sofia Wang, ensuring strategic leadership correspondence with ownership stakes totaling 100%.
- Lena Müller, a regular customer who appreciates conversations in German, underscores the restaurant’s linguistic adaptability through the staff’s diverse proficiency.
- Under the supervision of Juan Carlos, Federica Rossi brings charm to each dining experience, particularly during engaging community dinners for patrons.
- Chef Greta Nyman, a seasoned culinary artist, collaborates with Vinod Sharma in crafting the acclaimed Hearty Beef Stew, spotlighting a multicultural taste profile without allergenic components.
- Tables 15 and 16 facilitate an engaging atmosphere, critical for the “Cultural Dinner Exchange” event to foster intercultural dialogue.
- Joanne Lee, the bus driver, ensures smooth transit solutions complementing large group functionalities, demonstrating excellence in service beyond culinary offerings.
This instance delivers a unique setup for a culturally immersive dining experience, where structural variances in table capacity are utilized to their fullest potential to enhance event-driven restaurant operations. <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant24')
!restaurant24.name := 'Taste of Traditions'
!new Owner('owner50')
!owner50.name := 'Malik Sadiq'
!owner50.percentageShares := 33
!new Owner('owner51')
!owner51.name := 'Sofia Wang'
!owner51.percentageShares := 67
!insert (restaurant24, owner50) into RestaurantOwner
!insert (restaurant24, owner51) into RestaurantOwner
!new RegularCustomer('customer19')
!customer19.name := 'Lena Müller'
!customer19.prefferedLanguage := #German
!new HeadWaiter('headwaiter19')
!headwaiter19.name := 'Juan Carlos'
!headwaiter19.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!headwaiter19.phoneNumber := '1234567890' -- Arbitrary phone number
!new Waiter('waiter45')
!waiter45.name := 'Federica Rossi'
!waiter45.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!waiter45.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter45.spokenLanguage := #English
!insert (headwaiter19, waiter45) into HeadWaiterWaiter
!new Chef('chef26')
!chef26.name := 'Greta Nyman'
!chef26.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef26.phoneNumber := '3456789012' -- Arbitrary phone number
!new Cook('cook31')
!cook31.name := 'Vinod Sharma'
!cook31.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!cook31.phoneNumber := '4567890123' -- Arbitrary phone number
!cook31.yearsOfExperience := 7
!insert (chef26, cook31) into ChefCook
!new BusDriver('busdriver20')
!busdriver20.name := 'Joanne Lee'
!new Table('table61')
!table61.number := 15
!table61.description := 'Cozy corner booth'
!table61.capacity := 6
!new Table('table62')
!table62.number := 16
!table62.description := 'Community table'
!table62.capacity := 8
!new MenuItem('menuitem35')
!menuitem35.description := 'A rich and satisfying stew with seasonal vegetables.'
!menuitem35.prepTime := 35.0
!menuitem35.classification := #Main
!insert (menuitem35, chef26) into MenuItemChef
!new FoodItem('fooditem59')
!fooditem59.number := 59
!fooditem59.description := 'Beef Chunks'
!fooditem59.purchaseFlag := true
!fooditem59.unit := #Pound
!new FoodItem('fooditem60')
!fooditem60.number := 60
!fooditem60.description := 'Carrot'
!fooditem60.purchaseFlag := false
!fooditem60.unit := #Gram
!insert (menuitem35, fooditem59) into MenuItemFoodItem
!insert (menuitem35, fooditem60) into MenuItemFoodItem
!new Banquet('banquet20')
!banquet20.date := Date('2023-11-25')
!banquet20.time := Time('17:00')
!banquet20.groupName := 'Cultural Dinner Exchange'
!banquet20.numberPeople := 10
!banquet20.paymentMethod := #CreditCard
!insert (restaurant24, banquet20) into RestaurantReservation
!insert (banquet20, table61) into ReservationTable
!insert (banquet20, table62) into ReservationTable
!insert (banquet20, waiter45) into ReservationWaiter
!insert (banquet20, busdriver20) into BanquetBusDriver
!new ItemOrder('itemorder5')
!itemorder5.time := Time('17:20')
!insert (banquet20, itemorder5) into ReservationItemOrdered
!insert (itemorder5, menuitem35) into ItemOrderMenuItem
</object_model> LLM as a Judge
The object model correctly represents a real-world restaurant scenario. The owner shares sum up to exactly 100%, the tables assigned to the banquet have a total capacity of 14 which accommodates the 10 people assigned, prep times and time sequences are logical, and ingredients match their assigned menu item.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.24 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/75 |
| Multiplicities | 0/14 |
| Invariants | 0/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 88.5% |
| Shannon (Active) | 0.167 ± 0.373 |
| Shannon (All) | 0.072 ± 0.161 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 68.4% |
| Attributes | 62.1% |
| Relationships | 84.6% |
Uncovered Items 30
Show all 22 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 16/∞ |
| Attributes | 45/52 |
| Relationships | 14/∞ |
Viewer
!new Restaurant('restaurant23')
!restaurant23.name := 'Fusion Flavors'
!new Owner('owner48')
!owner48.name := 'Maria dos Santos'
!owner48.percentageShares := 60
!new Owner('owner49')
!owner49.name := 'Li Wei'
!owner49.percentageShares := 40
!insert (restaurant23, owner48) into RestaurantOwner
!insert (restaurant23, owner49) into RestaurantOwner
!new Chef('chef25')
!chef25.name := 'Pierre Laurent'
!chef25.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!chef25.phoneNumber := '1012345678' -- Arbitrary phone number
!new Cook('cook29')
!cook29.name := 'Haruto Tanaka'
!cook29.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook29.phoneNumber := '2012345678' -- Arbitrary phone number
!cook29.yearsOfExperience := 10
!new Cook('cook30')
!cook30.name := 'Fatima Zahra'
!cook30.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook30.phoneNumber := '3012345678' -- Arbitrary phone number
!cook30.yearsOfExperience := 3
!insert (chef25, cook29) into ChefCook
!insert (chef25, cook30) into ChefCook
!new Banquet('banquet19')
!banquet19.date := Date('2023-07-15')
!banquet19.time := Time('19:00')
!banquet19.groupName := 'Corporate Networking Gala'
!banquet19.numberPeople := 38
!banquet19.paymentMethod := #Cash
!insert (restaurant23, banquet19) into RestaurantReservation
!new Table('table59')
!table59.number := 30
!table59.description := 'Main hall with extensive projection facilities'
!table59.capacity := 40
!insert (banquet19, table59) into ReservationTable
!new BusDriver('busdriver19')
!busdriver19.name := 'Luca Fortunato'
!insert (banquet19, busdriver19) into BanquetBusDriver
!new HeadWaiter('headwaiter18')
!headwaiter18.name := 'Olivia Kim'
!headwaiter18.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter18.phoneNumber := '4012345678' -- Arbitrary phone number
!new Waiter('waiter42')
!waiter42.name := 'Carlos Mendes'
!waiter42.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter42.phoneNumber := '5012345678' -- Arbitrary phone number
!waiter42.spokenLanguage := #English
!new Waiter('waiter43')
!waiter43.name := 'Sofia Ivanova'
!waiter43.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter43.phoneNumber := '6012345678' -- Arbitrary phone number
!waiter43.spokenLanguage := #English
!insert (headwaiter18, waiter42) into HeadWaiterWaiter
!insert (headwaiter18, waiter43) into HeadWaiterWaiter
!insert (banquet19, waiter42) into ReservationWaiter
!insert (banquet19, waiter43) into ReservationWaiter
!new Individual('individualReservation12')
!individualReservation12.date := Date('2023-07-15')
!individualReservation12.time := Time('20:00')
!individualReservation12.numberPeople := 1
!individualReservation12.name := 'Ahmed Karim'
!individualReservation12.phoneNumber := '7001234567' -- Arbitrary phone number
!individualReservation12.seating := #Patio
!individualReservation12.smoking := #Smoking
!individualReservation12.number := 12
!insert (restaurant23, individualReservation12) into RestaurantReservation
!new Table('table60')
!table60.number := 18
!table60.description := 'Outdoor setting with garden lights'
!table60.capacity := 4
!insert (individualReservation12, table60) into ReservationTable
!new Waiter('waiter44')
!waiter44.name := 'John Doe'
!waiter44.dateOfBirth := Date('1978-01-01') -- Arbitrary date of birth
!waiter44.phoneNumber := '8001234567' -- Arbitrary phone number
!waiter44.spokenLanguage := #English
!insert (headwaiter18, waiter44) into HeadWaiterWaiter
!insert (individualReservation12, waiter44) into ReservationWaiter
!new MenuItem('menuitem33')
!menuitem33.description := 'Fusion dish combining sushi elements with a taco twist'
!menuitem33.prepTime := 25.0
!menuitem33.classification := #Apetizer
!insert (menuitem33, chef25) into MenuItemChef
!new FoodItem('fooditem54')
!fooditem54.number := 54
!fooditem54.description := 'Seaweed Wrap'
!fooditem54.unit := #Sheet
!new FoodItem('fooditem55')
!fooditem55.number := 55
!fooditem55.description := 'Assorted Fish'
!fooditem55.unit := #Gram
!new Allergen('allergen20')
!allergen20.type := #Seafood
!insert (fooditem55, allergen20) into FoodItemAllergen
!new FoodItem('fooditem56')
!fooditem56.number := 56
!fooditem56.description := 'Avocado'
!fooditem56.unit := #Gram
!insert (menuitem33, fooditem54) into MenuItemFoodItem
!insert (menuitem33, fooditem55) into MenuItemFoodItem
!insert (menuitem33, fooditem56) into MenuItemFoodItem
!new MenuItem('menuitem34')
!menuitem34.description := 'Crispy churros served with rich chocolate sauce'
!menuitem34.prepTime := 20.0
!menuitem34.classification := #Dessert
!insert (menuitem34, chef25) into MenuItemChef
!new FoodItem('fooditem57')
!fooditem57.number := 57
!fooditem57.description := 'Churro Dough'
!fooditem57.unit := #Pound
!new FoodItem('fooditem58')
!fooditem58.number := 58
!fooditem58.description := 'Dark Chocolate'
!fooditem58.unit := #Gram
!insert (menuitem34, fooditem57) into MenuItemFoodItem
!insert (menuitem34, fooditem58) into MenuItemFoodItem
!new Allergen('allergen21')
!allergen21.type := #Lactose
!insert (fooditem58, allergen21) into FoodItemAllergen
!new RegularCustomer('customer18')
!customer18.name := 'Ahmed Karim'
!customer18.prefferedLanguage := #English model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Complex Instance: Fusion Flavors
### Restaurant: "Fusion Flavors"
- **Name:** Fusion Flavors
- **Owners:**
1. **Owner Name:** Maria dos Santos
- **Percentage Shares:** 60%
- **Languages Spoken:** Portuguese, Spanish
2. **Owner Name:** Li Wei
- **Percentage Shares:** 40%
- **Languages Spoken:** English, Mandarin
- **Menus:**
1. **Chef:** Pierre Laurent
- **Languages Spoken:** French, English
- **Cook Team:**
- **Cook Name:** Haruto Tanaka
- **Years of Experience:** 10
- **Languages Spoken:** Japanese, English
- **Cook Name:** Fatima Zahra
- **Years of Experience:** 3
- **Languages Spoken:** Arabic, French
### Reservations
1. **Reservation (Banquet):**
- **Date:** July 15, 2023
- **Time:** 19:00
- **Group Name:** Corporate Networking Gala
- **Payment Method:** Cash
- **Assigned BusDriver:** Luca Fortunato
- **Languages Spoken:** Italian, English
- **Assigned Tables:**
- **Table 1:**
- **Number:** 30
- **Description:** Main hall with extensive projection facilities
- **Capacity:** 40
- **Total Attendees:** 38
- **Assigned Waiters:**
- **HeadWaiter:** Olivia Kim
- **Languages Spoken:** Korean, English
- **Waiters:**
- **Waiter Name:** Carlos Mendes
- **Languages Spoken:** Portuguese, English
- **Waiter Name:** Sofia Ivanova
- **Languages Spoken:** Russian, English
2. **Reservation (Individual):**
- **Date:** July 15, 2023
- **Time:** 20:00
- **Customer Name:** Ahmed Karim
- **Seating Preference:** Patio
- **Smoking Preference:** Smoking
- **Assigned Table:**
- **Number:** 18
- **Description:** Outdoor setting with garden lights
- **Capacity:** 4
- **Assigned Waiters:**
- **HeadWaiter:** Same as above
- **Waiter Name:** John Doe
- **Languages Spoken:** English, Spanish
### Menu Items
1. **Menu Item (Appetizer): Sushi Tacos**
- **Description:** Fusion dish combining sushi elements with a taco twist
- **Preparation Time:** 25 minutes
- **Chef:** Pierre Laurent (as above)
- **Food Items:**
- **FoodItem 1:** Seaweed Wrap
- **Unit:** Sheet
- **FoodItem 2:** Assorted Fish
- **Unit:** Gram
- **Dietary Requirements:** Halal
- **Allergens:**
- **Allergen Type:** Seafood
- **FoodItem 3:** Avocado
- **Unit:** Gram
2. **Menu Item (Dessert): Churros with Chocolate Ganache**
- **Description:** Crispy churros served with rich chocolate sauce
- **Preparation Time:** 20 minutes
- **Chef:** Pierre Laurent (as above)
- **Food Items:**
- **FoodItem 1:** Churro Dough
- **Unit:** Pound
- **FoodItem 2:** Dark Chocolate
- **Unit:** Gram
- **Allergen Type:** Lactose
### Dietary Requirements
- **RegularCustomer:** Ahmed Karim
- **Dietary Requirement:** Halal
- **Preferred Language:** Arabic
This instance showcases a vibrant fusion restaurant, blending diverse global cuisines such as Japanese and Mexican fusion appetizers, and Spanish dessert classics adapted for a multicultural clientele. The setting emphasizes both large corporate events and intimate dining, with careful attention to diverse dietary and cultural requirements. Fusion Flavors stands out with innovative culinary experiences and a multilingual, globally aware staff. The last output is partially incorrect:
temp.soil>
temp.soil> !insert (fooditem55, diet13) into FoodItemDietaryRequirement
<input>:1:0: Association `FoodItemDietaryRequirement' does not exist.
temp.soil> !customer18.name := 'Ahmed Karim'
temp.soil> !customer18.prefferedLanguage := #Arabic
<input>:1:0: generation of expression `#Arabic' failed, with following error:
<input>:1:33: Undefined enumeration literal `Arabic'.
temp.soil>
temp.soil> !insert (customer18, diet14) into DietaryRequirement
<input>:1:0: Association `DietaryRequirement' does not exist.
Please provide the complete output corrected <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant23')
!restaurant23.name := 'Fusion Flavors'
!new Owner('owner48')
!owner48.name := 'Maria dos Santos'
!owner48.percentageShares := 60
!new Owner('owner49')
!owner49.name := 'Li Wei'
!owner49.percentageShares := 40
!insert (restaurant23, owner48) into RestaurantOwner
!insert (restaurant23, owner49) into RestaurantOwner
!new Chef('chef25')
!chef25.name := 'Pierre Laurent'
!chef25.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!chef25.phoneNumber := '1012345678' -- Arbitrary phone number
!new Cook('cook29')
!cook29.name := 'Haruto Tanaka'
!cook29.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook29.phoneNumber := '2012345678' -- Arbitrary phone number
!cook29.yearsOfExperience := 10
!new Cook('cook30')
!cook30.name := 'Fatima Zahra'
!cook30.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook30.phoneNumber := '3012345678' -- Arbitrary phone number
!cook30.yearsOfExperience := 3
!insert (chef25, cook29) into ChefCook
!insert (chef25, cook30) into ChefCook
!new Banquet('banquet19')
!banquet19.date := Date('2023-07-15')
!banquet19.time := Time('19:00')
!banquet19.groupName := 'Corporate Networking Gala'
!banquet19.numberPeople := 38
!banquet19.paymentMethod := #Cash
!insert (restaurant23, banquet19) into RestaurantReservation
!new Table('table59')
!table59.number := 30
!table59.description := 'Main hall with extensive projection facilities'
!table59.capacity := 40
!insert (banquet19, table59) into ReservationTable
!new BusDriver('busdriver19')
!busdriver19.name := 'Luca Fortunato'
!insert (banquet19, busdriver19) into BanquetBusDriver
!new HeadWaiter('headwaiter18')
!headwaiter18.name := 'Olivia Kim'
!headwaiter18.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter18.phoneNumber := '4012345678' -- Arbitrary phone number
!new Waiter('waiter42')
!waiter42.name := 'Carlos Mendes'
!waiter42.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter42.phoneNumber := '5012345678' -- Arbitrary phone number
!waiter42.spokenLanguage := #English
!new Waiter('waiter43')
!waiter43.name := 'Sofia Ivanova'
!waiter43.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter43.phoneNumber := '6012345678' -- Arbitrary phone number
!waiter43.spokenLanguage := #English
!insert (headwaiter18, waiter42) into HeadWaiterWaiter
!insert (headwaiter18, waiter43) into HeadWaiterWaiter
!insert (banquet19, waiter42) into ReservationWaiter
!insert (banquet19, waiter43) into ReservationWaiter
!new Individual('individualReservation12')
!individualReservation12.date := Date('2023-07-15')
!individualReservation12.time := Time('20:00')
!individualReservation12.numberPeople := 1
!individualReservation12.name := 'Ahmed Karim'
!individualReservation12.phoneNumber := '7001234567' -- Arbitrary phone number
!individualReservation12.seating := #Patio
!individualReservation12.smoking := #Smoking
!individualReservation12.number := 12
!insert (restaurant23, individualReservation12) into RestaurantReservation
!new Table('table60')
!table60.number := 18
!table60.description := 'Outdoor setting with garden lights'
!table60.capacity := 4
!insert (individualReservation12, table60) into ReservationTable
!new Waiter('waiter44')
!waiter44.name := 'John Doe'
!waiter44.dateOfBirth := Date('1978-01-01') -- Arbitrary date of birth
!waiter44.phoneNumber := '8001234567' -- Arbitrary phone number
!waiter44.spokenLanguage := #English
!insert (headwaiter18, waiter44) into HeadWaiterWaiter
!insert (individualReservation12, waiter44) into ReservationWaiter
!new MenuItem('menuitem33')
!menuitem33.description := 'Fusion dish combining sushi elements with a taco twist'
!menuitem33.prepTime := 25.0
!menuitem33.classification := #Apetizer
!insert (menuitem33, chef25) into MenuItemChef
!new FoodItem('fooditem54')
!fooditem54.number := 54
!fooditem54.description := 'Seaweed Wrap'
!fooditem54.unit := #Sheet
!new FoodItem('fooditem55')
!fooditem55.number := 55
!fooditem55.description := 'Assorted Fish'
!fooditem55.unit := #Gram
!new Allergen('allergen20')
!allergen20.type := #Seafood
!insert (fooditem55, allergen20) into FoodItemAllergen
!new FoodItem('fooditem56')
!fooditem56.number := 56
!fooditem56.description := 'Avocado'
!fooditem56.unit := #Gram
!insert (menuitem33, fooditem54) into MenuItemFoodItem
!insert (menuitem33, fooditem55) into MenuItemFoodItem
!insert (menuitem33, fooditem56) into MenuItemFoodItem
!new MenuItem('menuitem34')
!menuitem34.description := 'Crispy churros served with rich chocolate sauce'
!menuitem34.prepTime := 20.0
!menuitem34.classification := #Dessert
!insert (menuitem34, chef25) into MenuItemChef
!new FoodItem('fooditem57')
!fooditem57.number := 57
!fooditem57.description := 'Churro Dough'
!fooditem57.unit := #Pound
!new FoodItem('fooditem58')
!fooditem58.number := 58
!fooditem58.description := 'Dark Chocolate'
!fooditem58.unit := #Gram
!insert (menuitem34, fooditem57) into MenuItemFoodItem
!insert (menuitem34, fooditem58) into MenuItemFoodItem
!new Allergen('allergen21')
!allergen21.type := #Lactose
!insert (fooditem58, allergen21) into FoodItemAllergen
!new RegularCustomer('customer18')
!customer18.name := 'Ahmed Karim'
!customer18.prefferedLanguage := #English
</object_model> LLM as a Judge
The object model correctly and logically instantiates the domain, strictly adhering to all multiplicity and OCL constraints. The attribute values closely resemble real-world data (e.g., table capacities accommodate the number of people, prep times are plausible, and the ownership shares explicitly sum to 100). Furthermore, the selected seating preference (`#Patio`) directly aligns with the assigned table's description ('Outdoor setting').
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.45 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/125 |
| Multiplicities | 0/24 |
| Invariants | 0/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 99.4% |
| String Equals | 99.8% |
| String LV | 86.8% |
| Shannon (Active) | 0.478 ± 0.480 |
| Shannon (All) | 0.265 ± 0.267 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 73.7% |
| Attributes | 74.1% |
| Relationships | 76.9% |
Uncovered Items 23
Show all 15 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 25/∞ |
| Attributes | 76/88 |
| Relationships | 24/∞ |
Viewer
!new Restaurant('restaurant26')
!restaurant26.name := 'Global Tastes Bistro'
!new Owner('owner54')
!owner54.name := 'Penelope Smith'
!owner54.percentageShares := 55
!new Owner('owner55')
!owner55.name := 'Yuko Yamada'
!owner55.percentageShares := 45
!insert (restaurant26, owner54) into RestaurantOwner
!insert (restaurant26, owner55) into RestaurantOwner
!new Banquet('banquet22')
!banquet22.date := Date('2024-11-23')
!banquet22.time := Time('18:30')
!banquet22.groupName := 'International Cultural Exchange Club'
!banquet22.numberPeople := 80
!banquet22.paymentMethod := #CreditCard
!insert (restaurant26, banquet22) into RestaurantReservation
!new Table('table66')
!table66.number := 1
!table66.description := 'Lotus Blossom'
!table66.capacity := 40
!new Table('table67')
!table67.number := 2
!table67.description := 'Amber Horizon'
!table67.capacity := 40
!insert (banquet22, table66) into ReservationTable
!insert (banquet22, table67) into ReservationTable
!new BusDriver('busdriver22')
!busdriver22.name := 'Tamara Kuznetsova'
!insert (banquet22, busdriver22) into BanquetBusDriver
!new HeadWaiter('headwaiter21')
!headwaiter21.name := 'Ilaria Bianchi'
!headwaiter21.dateOfBirth := Date('1982-01-01') -- Arbitrary date of birth
!headwaiter21.phoneNumber := '1234567890' -- Arbitrary phone number
!new Waiter('waiter48')
!waiter48.name := 'Jana Novak'
!waiter48.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter48.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter48.spokenLanguage := #English
!new Waiter('waiter49')
!waiter49.name := 'Miguel Diaz'
!waiter49.dateOfBirth := Date('1989-01-01') -- Arbitrary date of birth
!waiter49.phoneNumber := '3456789012' -- Arbitrary phone number
!waiter49.spokenLanguage := #English
!new Waiter('waiter50')
!waiter50.name := 'Soren Jensen'
!waiter50.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!waiter50.phoneNumber := '4567890123' -- Arbitrary phone number
!waiter50.spokenLanguage := #English
!insert (headwaiter21, waiter48) into HeadWaiterWaiter
!insert (headwaiter21, waiter49) into HeadWaiterWaiter
!insert (headwaiter21, waiter50) into HeadWaiterWaiter
!insert (banquet22, waiter48) into ReservationWaiter
!insert (banquet22, waiter49) into ReservationWaiter
!insert (banquet22, waiter50) into ReservationWaiter
!new Manager('manager5')
!manager5.name := 'Oliver Wang'
!manager5.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!manager5.phoneNumber := '5678901234' -- Arbitrary phone number
!new Chef('chef28')
!chef28.name := 'Nikolas Christos'
!chef28.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef28.phoneNumber := '6789012345' -- Arbitrary phone number
!new Cook('cook33')
!cook33.name := 'Eleni Papadopoulos'
!cook33.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook33.phoneNumber := '7890123456' -- Arbitrary phone number
!cook33.yearsOfExperience := 5
!insert (chef28, cook33) into ChefCook
!new MenuItem('menuitem38')
!menuitem38.description := 'Greek Spanakopita'
!menuitem38.prepTime := 25.0
!menuitem38.classification := #Apetizer
!insert (menuitem38, chef28) into MenuItemChef
!new Allergen('allergen23')
!allergen23.type := #Gluten
!new Allergen('allergen24')
!allergen24.type := #Lactose
!new Chef('chef29')
!chef29.name := 'Priya Shah'
!chef29.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef29.phoneNumber := '8901234567' -- Arbitrary phone number
!new Cook('cook34')
!cook34.name := 'Aakash Gupta'
!cook34.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!cook34.phoneNumber := '9012345678' -- Arbitrary phone number
!cook34.yearsOfExperience := 7
!insert (chef29, cook34) into ChefCook
!new MenuItem('menuitem39')
!menuitem39.description := 'Tandoori Lamb Chops'
!menuitem39.prepTime := 30.0
!menuitem39.classification := #Main
!insert (menuitem39, chef29) into MenuItemChef
!new Chef('chef30')
!chef30.name := 'Satoshi Hayashi'
!chef30.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef30.phoneNumber := '1234567891' -- Arbitrary phone number
!new Cook('cook35')
!cook35.name := 'Hinata Kojima'
!cook35.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook35.phoneNumber := '2345678902' -- Arbitrary phone number
!cook35.yearsOfExperience := 2
!insert (chef30, cook35) into ChefCook
!new MenuItem('menuitem40')
!menuitem40.description := 'Teriyaki Tofu Stir-Fry'
!menuitem40.prepTime := 20.0
!menuitem40.classification := #Main
!insert (menuitem40, chef30) into MenuItemChef
!new Cook('cook36')
!cook36.name := 'Fatima Hadi'
!cook36.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook36.phoneNumber := '3456789013' -- Arbitrary phone number
!cook36.yearsOfExperience := 6
!new Chef('chef31')
!chef31.name := 'Leila Fadila'
!chef31.dateOfBirth := Date('1978-01-01') -- Arbitrary date of birth
!chef31.phoneNumber := '4567890124' -- Arbitrary phone number
!insert (chef31, cook36) into ChefCook
!new MenuItem('menuitem41')
!menuitem41.description := 'Baklava with Honey'
!menuitem41.prepTime := 15.0
!menuitem41.classification := #Dessert
!insert (menuitem41, chef31) into MenuItemChef
!new Allergen('allergen25')
!allergen25.type := #Nuts
!new RegularCustomer('customer22')
!customer22.name := 'Lucas Hermann'
!customer22.prefferedLanguage := #German model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
**Instance: Cultural Exchange Dinner with Complex Staffing and Diverse Dietary Needs**
### Description
This instance describes a scenario where a local cultural exchange club hosts a dinner in a restaurant, bringing together people from diverse cultural backgrounds. The dinner is designed to embrace an array of dietary preferences and language needs, maximizing the complexity of staffing and customer interaction.
---
**Restaurant: Global Tastes Bistro**
- Name: Global Tastes Bistro
- Owners:
- **Owner1:** Penelope Smith, 55% shares
- **Owner2:** Yuko Yamada, 45% shares
- Total shares: 100% (constraint met)
---
**Reservation: Cultural Exchange Club Dinner**
- Type: Banquet
- Date: 2024-11-23 (to coincide with a local cultural festival)
- Time: 18:30
- Customer: International Cultural Exchange Club
- Group Size: 80
- Payment Methods: CreditCard, Cash
- Regular Customer Associated: Lucas Hermann (Preferred Language: German)
---
**Table Assignments**
- **Table1:**
- Description: "Lotus Blossom"
- Capacity: 40
- **Table2:**
- Description: "Amber Horizon"
- Capacity: 40
- Total Capacity: 80 (meets constraint for banquet seating)
---
**Personnel**
- **BusDriver:** Tamara Kuznetsova, responsible for transporting guests to the banquet.
- **Waiters:**
- Jana Novak (Language: Czech, English)
- Miguel Diaz (Language: Spanish, Portuguese)
- Soren Jensen (Language: Danish, English)
- **HeadWaiter:** Ilaria Bianchi
- Manages all waiters, speaks Italian, French
- **Manager:** Oliver Wang
- Speaks Chinese, English
---
**Menu and Kitchen Staff**
- **MenuItems:**
- **Appetizer:** Greek Spanakopita
- Designed by Chef Nikolas Christos
- Dietary: Vegetarian
- Allergen: Gluten, Lactose
- **Main Dish 1:** Tandoori Lamb Chops
- Designed by Chef Priya Shah
- Dietary: Halal
- Allergen: None
- **Main Dish 2:** Teriyaki Tofu Stir-Fry
- Designed by Chef Satoshi Hayashi
- Dietary: Vegan, Gluten-free
- Allergen: Soy
- **Dessert:** Baklava with Honey
- Designed by Chef Leila Fadila
- Dietary: Kosher
- Allergen: Nuts
- **Cooks:**
- Cook under Nikolas Christos: Eleni Papadopoulos (Greek)
- Cook under Priya Shah: Aakash Gupta (Hindi)
- Cook under Satoshi Hayashi: Hinata Kojima (Japanese)
- Cook under Leila Fadila: Fatima Hadi (Arabic)
- **Chefs Overseeing Items:**
- **Chef Nikolas Christos**
- Supervises 1 Cook
- Languages: Greek, English
- **Chef Priya Shah**
- Supervises 1 Cook
- Languages: Hindi, English
- **Chef Satoshi Hayashi**
- Supervises 1 Cook
- Languages: Japanese, English
- **Chef Leila Fadila**
- Supervises 1 Cook
- Languages: Arabic, French
---
### Uncommon Aspects:
- A banquet catering to an event based on cultural celebration and exchange, uniting multiple culinary traditions into a single, cohesive menu.
- Attendance by a diverse cultural exchange club with linguistic diversity across patrons and staff to facilitate optimal experience.
- Offering multiple main courses to cater to varied dietary preferences, blending halal, vegan, vegetarian, and kosher options for inclusivity.
- The event coincides with a local cultural festival, highlighting the restaurant’s engagement with the local community.
This instance captures a complex logistical arrangement designed to foster inclusivity and celebrate cultural diversity, emphasizing the strategic and operational capabilities of the restaurant management system. <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant26')
!restaurant26.name := 'Global Tastes Bistro'
!new Owner('owner54')
!owner54.name := 'Penelope Smith'
!owner54.percentageShares := 55
!new Owner('owner55')
!owner55.name := 'Yuko Yamada'
!owner55.percentageShares := 45
!insert (restaurant26, owner54) into RestaurantOwner
!insert (restaurant26, owner55) into RestaurantOwner
!new Banquet('banquet22')
!banquet22.date := Date('2024-11-23')
!banquet22.time := Time('18:30')
!banquet22.groupName := 'International Cultural Exchange Club'
!banquet22.numberPeople := 80
!banquet22.paymentMethod := #CreditCard
!insert (restaurant26, banquet22) into RestaurantReservation
!new Table('table66')
!table66.number := 1
!table66.description := 'Lotus Blossom'
!table66.capacity := 40
!new Table('table67')
!table67.number := 2
!table67.description := 'Amber Horizon'
!table67.capacity := 40
!insert (banquet22, table66) into ReservationTable
!insert (banquet22, table67) into ReservationTable
!new BusDriver('busdriver22')
!busdriver22.name := 'Tamara Kuznetsova'
!insert (banquet22, busdriver22) into BanquetBusDriver
!new HeadWaiter('headwaiter21')
!headwaiter21.name := 'Ilaria Bianchi'
!headwaiter21.dateOfBirth := Date('1982-01-01') -- Arbitrary date of birth
!headwaiter21.phoneNumber := '1234567890' -- Arbitrary phone number
!new Waiter('waiter48')
!waiter48.name := 'Jana Novak'
!waiter48.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter48.phoneNumber := '2345678901' -- Arbitrary phone number
!waiter48.spokenLanguage := #English
!new Waiter('waiter49')
!waiter49.name := 'Miguel Diaz'
!waiter49.dateOfBirth := Date('1989-01-01') -- Arbitrary date of birth
!waiter49.phoneNumber := '3456789012' -- Arbitrary phone number
!waiter49.spokenLanguage := #English
!new Waiter('waiter50')
!waiter50.name := 'Soren Jensen'
!waiter50.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!waiter50.phoneNumber := '4567890123' -- Arbitrary phone number
!waiter50.spokenLanguage := #English
!insert (headwaiter21, waiter48) into HeadWaiterWaiter
!insert (headwaiter21, waiter49) into HeadWaiterWaiter
!insert (headwaiter21, waiter50) into HeadWaiterWaiter
!insert (banquet22, waiter48) into ReservationWaiter
!insert (banquet22, waiter49) into ReservationWaiter
!insert (banquet22, waiter50) into ReservationWaiter
!new Manager('manager5')
!manager5.name := 'Oliver Wang'
!manager5.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!manager5.phoneNumber := '5678901234' -- Arbitrary phone number
!new Chef('chef28')
!chef28.name := 'Nikolas Christos'
!chef28.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef28.phoneNumber := '6789012345' -- Arbitrary phone number
!new Cook('cook33')
!cook33.name := 'Eleni Papadopoulos'
!cook33.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook33.phoneNumber := '7890123456' -- Arbitrary phone number
!cook33.yearsOfExperience := 5
!insert (chef28, cook33) into ChefCook
!new MenuItem('menuitem38')
!menuitem38.description := 'Greek Spanakopita'
!menuitem38.prepTime := 25.0
!menuitem38.classification := #Apetizer
!insert (menuitem38, chef28) into MenuItemChef
!new Allergen('allergen23')
!allergen23.type := #Gluten
!new Allergen('allergen24')
!allergen24.type := #Lactose
!new Chef('chef29')
!chef29.name := 'Priya Shah'
!chef29.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef29.phoneNumber := '8901234567' -- Arbitrary phone number
!new Cook('cook34')
!cook34.name := 'Aakash Gupta'
!cook34.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!cook34.phoneNumber := '9012345678' -- Arbitrary phone number
!cook34.yearsOfExperience := 7
!insert (chef29, cook34) into ChefCook
!new MenuItem('menuitem39')
!menuitem39.description := 'Tandoori Lamb Chops'
!menuitem39.prepTime := 30.0
!menuitem39.classification := #Main
!insert (menuitem39, chef29) into MenuItemChef
!new Chef('chef30')
!chef30.name := 'Satoshi Hayashi'
!chef30.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef30.phoneNumber := '1234567891' -- Arbitrary phone number
!new Cook('cook35')
!cook35.name := 'Hinata Kojima'
!cook35.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook35.phoneNumber := '2345678902' -- Arbitrary phone number
!cook35.yearsOfExperience := 2
!insert (chef30, cook35) into ChefCook
!new MenuItem('menuitem40')
!menuitem40.description := 'Teriyaki Tofu Stir-Fry'
!menuitem40.prepTime := 20.0
!menuitem40.classification := #Main
!insert (menuitem40, chef30) into MenuItemChef
!new Cook('cook36')
!cook36.name := 'Fatima Hadi'
!cook36.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook36.phoneNumber := '3456789013' -- Arbitrary phone number
!cook36.yearsOfExperience := 6
!new Chef('chef31')
!chef31.name := 'Leila Fadila'
!chef31.dateOfBirth := Date('1978-01-01') -- Arbitrary date of birth
!chef31.phoneNumber := '4567890124' -- Arbitrary phone number
!insert (chef31, cook36) into ChefCook
!new MenuItem('menuitem41')
!menuitem41.description := 'Baklava with Honey'
!menuitem41.prepTime := 15.0
!menuitem41.classification := #Dessert
!insert (menuitem41, chef31) into MenuItemChef
!new Allergen('allergen25')
!allergen25.type := #Nuts
!new RegularCustomer('customer22')
!customer22.name := 'Lucas Hermann'
!customer22.prefferedLanguage := #German
</object_model> LLM as a Judge
The object model represents a highly logically consistent and plausible scenario. The ages, experience levels, and designations of the restaurant staff are perfectly normal. The table capacities accurately accommodate the exact number of people attending the banquet. The ownership shares sum up to 100%, and the relationships between chefs, their culturally appropriate menu items, and their supervising cooks make real-world semantic sense.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.26 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/128 |
| Multiplicities | 0/20 |
| Invariants | 0/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 98.1% |
| String Equals | 100.0% |
| String LV | 87.6% |
| Shannon (Active) | 0.324 ± 0.459 |
| Shannon (All) | 0.257 ± 0.364 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 68.4% |
| Attributes | 60.3% |
| Relationships | 61.5% |
Uncovered Items 34
Show all 23 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 28/∞ |
| Attributes | 80/87 |
| Relationships | 20/∞ |
Viewer
!new Restaurant('restaurant17')
!restaurant17.name := 'World Flavors'
!new Owner('owner35')
!owner35.name := 'Chiara Rossi'
!owner35.percentageShares := 55
!new Owner('owner36')
!owner36.name := 'Akio Tanaka'
!owner36.percentageShares := 45
!insert (restaurant17, owner35) into RestaurantOwner
!insert (restaurant17, owner36) into RestaurantOwner
!new Banquet('banquet14')
!banquet14.date := Date('2023-09-15')
!banquet14.time := Time('12:00')
!banquet14.groupName := 'International Language Club'
!banquet14.numberPeople := 40
!banquet14.paymentMethod := #Cash
!insert (restaurant17, banquet14) into RestaurantReservation
!new Table('table44')
!table44.number := 501
!table44.description := 'Elegant long table'
!table44.capacity := 18
!new Table('table45')
!table45.number := 502
!table45.description := 'Charming café table'
!table45.capacity := 8
!new Table('table46')
!table46.number := 503
!table46.description := 'Cozy corner table'
!table46.capacity := 6
!insert (banquet14, table44) into ReservationTable
!insert (banquet14, table45) into ReservationTable
!insert (banquet14, table46) into ReservationTable
!new BusDriver('busdriver14')
!busdriver14.name := 'Leila Abadi'
!insert (banquet14, busdriver14) into BanquetBusDriver
!new Waiter('waiter29')
!waiter29.name := 'Elena Garcia'
!waiter29.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter29.phoneNumber := '1234567890' -- Arbitrary phone number
!waiter29.spokenLanguage := #English
!new Waiter('waiter30')
!waiter30.name := 'Sanjay Patel'
!waiter30.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter30.phoneNumber := '0987654321' -- Arbitrary phone number
!waiter30.spokenLanguage := #English
!new Waiter('waiter31')
!waiter31.name := 'Amelie Dupont'
!waiter31.dateOfBirth := Date('1997-01-01') -- Arbitrary date of birth
!waiter31.phoneNumber := '1122334455' -- Arbitrary phone number
!waiter31.spokenLanguage := #English
!insert (banquet14, waiter29) into ReservationWaiter
!insert (banquet14, waiter30) into ReservationWaiter
!insert (banquet14, waiter31) into ReservationWaiter model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople You are tasked with analyzing conceptual models represented as class diagrams and expressed in the UML-based specification environment using its native syntax. You must adhere to the following requirements: - Use very clear language. - Do not overexplain, be concise. - Multiplicities must be very clear and easy to understand. You should follow the structure and requirements below: ## Description Start by explaining the overall structure and purpose of the model. ### Components Break down the components of the model (i.e., classes and attributes), describing each, their type and purpose. ## Relationships Describe the relationships between the components of the model, dependencies and multiplicities (i.e., minimum and maximum number of instances of one class that can be associated with instances of another class). Describe the multiplicities at both ends of each association. ## Invariants Define the invariants that apply to the model (i.e., those constraints that must be fulfilled). Your task is to generate a complete and diverse instance, in plain English, for a given category and based on a provided conceptual model description. The instance must adhere to these requirements: - Be self-contained: Include all required attributes, relationships, and related entities in full detail. - Conform to the model: Fulfill the constraints, multiplicities, relationships, and attributes defined in the class diagram model. - Understand the context: Ensure that its attributes and relationships are relevant. - Avoid duplication of instances: Take into consideration those instances previously built to avoid redundancy. - Semantic diversity: From a semantic point of view, incorporate varied scenarios, including regional, linguistic, or cultural differences. - Structural diversity: Include instances with different numbers of elements, different numbers of relationships and complexity, and create varied examples by changing entity attributes. You are tasked with creating instances of a conceptual model in the UML-based Specification Environment (USE). You will receive: 1. The UML class diagram that the instance follows. 2. A sample syntax of instances creation. 3. A description of the instance that needs to be created. Your goal is to generate these instances based on the provided description, adhering strictly to these requirements: - The output must be in plain text, with no additional comments, descriptions, or explanations. - Ensure that the created instance adheres to the provided description. - Follow the syntax sample provided, without deviation. - Take into account previously created instances to avoid using duplicate naming. <role>
You are an expert software and system modeler. You are able to assess the semantic quality of object models that have been created to conform to a domain model. The models are defined in USE (UML-based Specification Environment) and OCL (Object Constraint Language).
Your primary capability is "Semantic Reality Checking". You do not just check for syntactic correctness; you check for real-world plausibility and logical consistency within a given domain.
</role>
<context>
The user will provide two types of content:
1. **Domain Model (.use)**: A class diagram definition including classes, attributes, enums, relationships, multiplicities and roles.
2. **Object Model (.soil)**: An object model. This object model can be seen as a script composed of instructions for the creation of objects, relationships and setting attribute values (snapshot).
Your goal is to act as a judge to determine if the object model represents a **REALISTIC** scenario based on the domain model and common sense real-world logic.
</context>
<definitions>
- **Realistic**: The object model is syntactically correct AND semantically plausible (e.g., A 'Person' has an age between 0 and 120; a 'Car' has a positive price).
- **Unrealistic**: The object model contains contradictions, impossible physical values, or nonsensical relationships (e.g., A 'Person' is their own father; a 'Product' has a negative weight).
- **Doubtful**: You cannot determine whether the object model is realistic or not.
</definitions>
<instructions>
Follow this thinking process strictly before generating the final output:
1. **Analyze the Domain (.use)**: Understand the classes and what they represent in the real world.
2. **Analyze the Instances (.soil)**: Map the created objects to their classes. Look at the specific values assigned to attributes and the relationships created between objects.
3. **Evaluate Semantics**:
- Apply "Common Sense Knowledge" to the attribute values.
- Check cardinality and relationship logic beyond simple OCL constraints.
- Identify any outliers or logical fallacies.
4. **Determine Verdict**: Select one of the defined labels (Realistic/Unrealistic/Doubtful).
</instructions>
<constraints>
- **Tone**: Objective, Analytical, Technical.
- **Verbosity**: Low. Be direct.
- **Reasoning**: The "Why" section must be concise and specific, citing variable names, objects, or relationships when possible.
- Do not output the internal thinking process. Only output the final formatted result.
</constraints>
<output_format>
Structure your response exactly as follows:
**Response**: [Realistic | Unrealistic | Doubtful]
**Why**: [Concise explanation of your reasoning. If Unrealistic, specify the exact objects, values or relationships that break realism.]
</output_format>
<examples>
Example 1:
Input:
<domain_model>
class Person
attributes
age: Integer
end
class Pet
attributes
name: String
end
association Ownership between
Person [1] role owner
Pet [*] role pets
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 250
!new Pet('pet1')
!pet1.name := 'Luna'
… 1.000 more pets creation …
!pet1000.name := 'Max'
!insert (p1, pet1) into Ownership
…1.000 more pets associated with p1 …
!insert (p1, pet1000) into Ownership
</object_model>
Output:
**Response**: Unrealistic
**Why**: The object 'p1' of class 'Person' has an age of 250, which exceeds the biologically plausible lifespan of a human. Although it is not plausible that 1 same person owns 1.000 pets.
Example 2:
Input:
<domain_model>
class Car
attributes
brand: String
end
class Person
attributes
name: String
end
association Ownership between
Person [1] role owner
Car [*] role cars
end
</domain_model>
<object_model>
!new Person('p1')
!p1.age := 19
!new Car('c1')
!c1.brand := 'Toyota'
!insert (p1, c1) into Ownership
</object_model>
Output:
**Response**: Realistic
**Why**: The object 'c1' has a valid, recognized real-world car brand assigned, and its plausible that a teenager has only one car.
Example 3:
Input:
<domain_model>
class Component
attributes
setting_val: Integer
config_mode: String
end
</domain_model>
<object_model>
!new Component('c1')
!c1.setting_val := 8080
!c1.config_mode := 'Legacy'
</object_model>
Output:
**Response**: Doubtful
**Why**: The class 'Component' and attribute 'setting_val' are generic and lack specific real-world semantic context. Without knowing what specific physical or software system this represents, it is impossible to determine if '8080' is a realistic value or an outlier.
</examples> Analyze the following UML class diagram:
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople For the same category and model description, generate another instance that is structurally and semantically different from the previous ones Continue with the following description, creating the instance according to the syntax example and this specification:
## Instance: Cultural Exchange Luncheon at "World Flavors"
### Entities:
1. **Restaurant:**
- Name: World Flavors
2. **Owner:**
- Name: Chiara Rossi
- Percentage Shares: 55%
3. **Owner:**
- Name: Akio Tanaka
- Percentage Shares: 45%
4. **Banquet (Reservation):**
- Date: "2023-09-15"
- Time: "12:00"
- Group Name: International Language Club
- Number of People: 40
- Payment Method: Cash
5. **Table (Assigned to Banquet):**
- Number: T501
- Description: Elegant long table
- Capacity: 18
6. **Table (Assigned to Banquet):**
- Number: T502
- Description: Charming café table
- Capacity: 8
7. **Table (Assigned to Banquet):**
- Number: T503
- Description: Cozy corner table
- Capacity: 6
8. **BusDriver:**
- Name: Leila Abadi
- Language: Farsi, English
9. **Waiter:**
- Name: Elena Garcia
- Languages Spoken: Spanish, French, English
- Years of Experience: 8
10. **Waiter:**
- Name: Sanjay Patel
- Languages Spoken: Hindi, English
- Years of Experience: 5
11. **Waiter:**
- Name: Amelie Dupont
- Languages Spoken: French, English
- Years of Experience: 2
### Relationships:
1. **Restaurant-Owner (RestaurantOwner):**
- World Flavors - Chiara Rossi
- World Flavors - Akio Tanaka
2. **Restaurant-Reservation (RestaurantReservation):**
- World Flavors - International Language Club Banquet
3. **Banquet-BusDriver (BanquetBusDriver):**
- International Language Club - Leila Abadi
4. **Reservation-Table (ReservationTable - Violates Constraint):**
- International Language Club is assigned with T501, T502, T503
5. **Reservation-Waiter (ReservationWaiter - Unexpected Real-Life Issue):**
- International Language Club Banquet served by Elena Garcia, Sanjay Patel, Amelie Dupont
### Explanation of Overconstraint Detection:
This scenario involves a Cultural Exchange Luncheon for the International Language Club hosted at World Flavors. The banquet is intended for 40 guests, but the available seating from tables T501, T502, and T503 does not suffice, offering only a total capacity of 32, thus violating the 'TablesCapacityGreaterThanPeople' constraint.
Although this instance correctly assigns three waiters to serve the banquet, aligning with the model's requirement of 1 or more waiters per event, it poses practical challenges in ensuring an equitable distribution of service among a diverse linguistic group, which is a contextual operational difficulty not explicitly covered by current multiplicity rules, showing a gap in addressing cultural complexity versus service logistics. <domain_model>
model Restaurant
dataType Date
operations
Date (date : String)
end
dataType Time
operations
Time (time : String)
end
enum SeatingPreference {
Inside,
Patio
}
enum SmokingPreference {
Smoking,
NonSmoking
}
enum PaymentMethod {
Cash,
CreditCard
}
enum ItemType {
Apetizer,
Main,
Dessert,
Beverage
}
enum UnitOfMeasure {
Ounce,
Sheet,
Pound,
Gram,
Dozen
}
enum AllergenType {
Lactose,
Seafood,
Nuts,
Gluten
}
enum Diet {
Vegetarian,
Vegan,
Kosher,
Halal
}
enum Language {
English,
Spanish,
German,
Italian
}
class Restaurant
attributes
name : String
end
abstract class Reservation
attributes
time : Time
date : Date
numberPeople : Integer
name : String
phoneNumber : String
number : Integer
end
class Individual < Reservation
attributes
seating : SeatingPreference
smoking : SmokingPreference
end
class Banquet < Reservation
attributes
groupName : String
paymentMethod : PaymentMethod
busService : Boolean
end
class Table
attributes
number : Integer
description : String
capacity : Integer
end
class ItemOrder
attributes
time : Time
end
class MenuItem
attributes
description : String
prepTime : Real
classification : ItemType
end
class FoodItem
attributes
number : Integer
description : String
purchaseFlag : Boolean
unit : UnitOfMeasure
end
class Allergen
attributes
type : AllergenType
end
class Person
attributes
name : String
end
class Owner < Person
attributes
percentageShares : Integer
end
class RegularCustomer < Person
attributes
prefferedLanguage : Language
end
class DietaryRequirement
attributes
diet : Diet
end
class ReportedAllergy
attributes
allergen : AllergenType
end
abstract class Worker < Person
attributes
dateOfBirth : Date
phoneNumber : String
end
class HeadWaiter < Worker
end
class Waiter < Worker
attributes
spokenLanguage : Language
end
class Manager < Worker
end
class Cook < Worker
attributes
yearsOfExperience : Integer
end
class Chef < Worker
end
class BusDriver < Worker
attributes
driverLicenseNr : String
end
association RestaurantOwner between
Restaurant [1..*]
Owner [1..*]
end
association RestaurantReservation between
Restaurant [0..1]
Reservation [0..*]
end
association ReservationCustomer between
Reservation [0..*]
RegularCustomer [0..1]
end
association ReservationWaiter between
Reservation [*]
Waiter [1..*] role servedBy
end
association BanquetBusDriver between
Banquet [1]
BusDriver [0..*]
end
association ReservationTable between
Reservation [1]
Table [1..*] role assignedTo
end
association ReservationItemOrdered between
Reservation [1]
ItemOrder [0..*]
end
association ItemOrderMenuItem between
ItemOrder [*]
MenuItem [1] role item
end
association MenuItemFoodItem between
MenuItem [*] role isUtilized
FoodItem [*] role utilizes
end
association FoodItemAllergen between
FoodItem [*]
Allergen [*] role contains
end
association MenuItemChef between
MenuItem [*] role designs
Chef [1] role designedBy
end
association ChefCook between
Chef [1] role underSupervisionOf
Cook [1..*] role supervises
end
association HeadWaiterWaiter between
HeadWaiter [1]
Waiter [1..*] role responsibleFor
end
constraints
context Table inv PositiveCapacity:
self.capacity > 0
context Cook inv PositiveExperience:
self.yearsOfExperience >= 0
context Restaurant inv TotalOwnerShares:
self.owner -> collect(o | o.percentageShares) -> sum() = 100
context Reservation inv TablesCapacityGreaterThanPeople:
self.assignedTo -> collect(t | t.capacity) -> sum() >= self.numberPeople
</domain_model>
<object_model>
!new Restaurant('restaurant17')
!restaurant17.name := 'World Flavors'
!new Owner('owner35')
!owner35.name := 'Chiara Rossi'
!owner35.percentageShares := 55
!new Owner('owner36')
!owner36.name := 'Akio Tanaka'
!owner36.percentageShares := 45
!insert (restaurant17, owner35) into RestaurantOwner
!insert (restaurant17, owner36) into RestaurantOwner
!new Banquet('banquet14')
!banquet14.date := Date('2023-09-15')
!banquet14.time := Time('12:00')
!banquet14.groupName := 'International Language Club'
!banquet14.numberPeople := 40
!banquet14.paymentMethod := #Cash
!insert (restaurant17, banquet14) into RestaurantReservation
!new Table('table44')
!table44.number := 501
!table44.description := 'Elegant long table'
!table44.capacity := 18
!new Table('table45')
!table45.number := 502
!table45.description := 'Charming café table'
!table45.capacity := 8
!new Table('table46')
!table46.number := 503
!table46.description := 'Cozy corner table'
!table46.capacity := 6
!insert (banquet14, table44) into ReservationTable
!insert (banquet14, table45) into ReservationTable
!insert (banquet14, table46) into ReservationTable
!new BusDriver('busdriver14')
!busdriver14.name := 'Leila Abadi'
!insert (banquet14, busdriver14) into BanquetBusDriver
!new Waiter('waiter29')
!waiter29.name := 'Elena Garcia'
!waiter29.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter29.phoneNumber := '1234567890' -- Arbitrary phone number
!waiter29.spokenLanguage := #English
!new Waiter('waiter30')
!waiter30.name := 'Sanjay Patel'
!waiter30.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter30.phoneNumber := '0987654321' -- Arbitrary phone number
!waiter30.spokenLanguage := #English
!new Waiter('waiter31')
!waiter31.name := 'Amelie Dupont'
!waiter31.dateOfBirth := Date('1997-01-01') -- Arbitrary date of birth
!waiter31.phoneNumber := '1122334455' -- Arbitrary phone number
!waiter31.spokenLanguage := #English
!insert (banquet14, waiter29) into ReservationWaiter
!insert (banquet14, waiter30) into ReservationWaiter
!insert (banquet14, waiter31) into ReservationWaiter
</object_model> LLM as a Judge
The 'banquet14' reservation is for 40 people, but the total capacity of the assigned tables ('table44', 'table45', 'table46') is only 32 (18 + 8 + 6). This means there are not enough seats for the guests, violating common sense and the domain constraint.
Metrics
Stats
Stats Breakdown of the total cost and elapsed time for generating the instances. - Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
- Elapsed Time = Console Time (ie. Processing Time + API Calls)
- Cost = (input tokens * input price) + (output tokens * output price)
| Total Cost | $0.17 |
Validation
Validation Measures the correctness of the instantiation using the USE check function. - Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
- Syntax = 1 - (Total Number of syntax errors [use check] / Total Number of lines [instance])
- Multiplicities = 1 - (Total Number of multiplicities errors [use check] / Total Number of relationships ([instance] !insert))
- Invariants = 1 - (Total Number of invariants errors [use check] / Total Number of invariants ([model] constraints))
| Syntax | 0/53 |
| Multiplicities | 3/10 |
| Invariants | 1/4 |
Diversity
Diversity Measures the variability of the generated instances. Attributes (NumericEquals, StringEquals, StringLv): It identifies how much the LLM repeats specific values versus generating unique data points across instances (100%: Diverse, 0%: Repetitive). We group all generated attributes into bags (numeric and string) and then perform pairwise comparisons between every element to obtain. Structure (GED): Measures the Graph Edit Distance (GED) similarity between instances. Distribution (Shannon): Measures the entropy and evenness (balanced distribution) of the generated enum values. - NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
- NumericEquals = Total number of numeric attribute pairs with different values / Total number of possible pairs (n * (n - 1) / 2)
- StringEquals = Total number of string attribute pairs that are NOT exactly identical / Total number of possible pairs (n * (n - 1) / 2)
- StringLv = Sum of (Levenshtein Distance(a, b) / max(length(a), length(b))) for all string pairs / Total number of possible pairs (n * (n - 1) / 2)
- GED = Similarity = 1 - (GED / (0.5 * (GED_to_empty_A + GED_to_empty_B))). 1 = red = identical graphs, <=0.5 = green = different graphs. We consider as edit operations: Nodes, Edges, Node_Labels and Edge_Labels [https://github.com/a-coman/ged]
- Shannon (Active) = Entropy / log2(Number of unique groups actually generated). Measures how evenly the generated values are distributed, considering only the categories the LLM actually used.
- Shannon (All) = Entropy / log2(Total number of valid groups defined in the model). Measures how evenly the generated values are distributed against the full spectrum of all possible valid options defined in the .use file.
| Numeric | 100.0% |
| String Equals | 100.0% |
| String LV | 89.0% |
| Shannon (Active) | 0.000 ± 0.000 |
| Shannon (All) | 0.000 ± 0.000 |
Coverage
Model Coverage Measures the breadth of the instantiation. It answers: "How much of the structural blueprint (the model) was used?" - Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
- Classes = Total Unique Classes instantiated (!new) in the .soil / Total Number of classes (class) in the model .use
- Attributes = Total Unique Attributes instantiated (!Class.Attribute or !set) in the .soil / Total Number of attributes (attributes) in the model .use
- Relationships = Total Unique Relationships instantiated (!insert) in the .soil / Total Number of relationships (association, composition, aggregation) in the model .use
| Classes | 31.6% |
| Attributes | 27.6% |
| Relationships | 38.5% |
Uncovered Items 63
Show all 13 classes
Show all 42 attributes
Instantiation
Instance Instantiation Measures the depth or density of the data. It answers: "Of the objects the LLM decided to create, how many of their available 'slots' did it fill?" - Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
- Classes = Total Number of classes (!new) in the instance / Total possible that could have been instantiated (infinity)
- Attributes = Total Number of attributes (!Class.Attribute or !set) in the instance / Total possible that could have been instantiated (sum(number of classes instantiated of that type * Class.Attributes))
- Relationships = Total Number of relationships (!insert) in the instance / Total possible that could have been instantiated (infinity)
| Classes | 11/∞ |
| Attributes | 32/39 |
| Relationships | 10/∞ |