Restaurant / gen4
Viewer
!new Restaurant('restaurant4')
!restaurant4.name := 'Spice Symphony'
!new Owner('owner8')
!owner8.name := 'Nina Simone'
!owner8.percentageShares := 50
!insert (restaurant4, owner8) into RestaurantOwner
!new Owner('owner9')
!owner9.name := 'Henry Lee'
!owner9.percentageShares := 50
!insert (restaurant4, owner9) into RestaurantOwner
!new Table('table8')
!table8.number := 8
!table8.description := 'Long family table'
!table8.capacity := 12
!new Table('table9')
!table9.number := 9
!table9.description := 'Intimate booth'
!table9.capacity := 4
!new Table('table10')
!table10.number := 10
!table10.description := 'Outdoor dining'
!table10.capacity := 16
!new RegularCustomer('customer5')
!customer5.name := 'Olivia Benson'
!customer5.prefferedLanguage := #Spanish
!new Waiter('waiter6')
!waiter6.name := 'Carlos Ruiz'
!waiter6.dateOfBirth := Date('1993-04-14')
!waiter6.phoneNumber := '555-9988'
!waiter6.spokenLanguage := #English
!new HeadWaiter('headwaiter4')
!headwaiter4.name := 'Samantha Brown'
!headwaiter4.dateOfBirth := Date('1981-09-20')
!headwaiter4.phoneNumber := '555-4433'
!insert (headwaiter4, waiter6) into HeadWaiterWaiter
!new Individual('reservation5')
!reservation5.time := Time('20:00')
!reservation5.date := Date('2023-12-24')
!reservation5.numberPeople := 2
!reservation5.name := 'Olivia Benson'
!reservation5.phoneNumber := '555-7766'
!reservation5.number := 5
!reservation5.seating := #Inside
!reservation5.smoking := #NonSmoking
!insert (restaurant4, reservation5) into RestaurantReservation
!insert (reservation5, customer5) into ReservationCustomer
!insert (reservation5, waiter6) into ReservationWaiter
!insert (reservation5, table9) into ReservationTable
!new Banquet('reservation6')
!reservation6.time := Time('19:00')
!reservation6.date := Date('2023-12-31')
!reservation6.numberPeople := 25
!reservation6.name := 'New Year Party'
!reservation6.phoneNumber := '555-4567'
!reservation6.number := 6
!reservation6.groupName := 'Celebration Group'
!reservation6.paymentMethod := #CreditCard
!reservation6.busService := true
!insert (restaurant4, reservation6) into RestaurantReservation
!insert (reservation6, table8) into ReservationTable
!insert (reservation6, table10) into ReservationTable
!insert (reservation6, waiter6) into ReservationWaiter
!new BusDriver('busdriver3')
!busdriver3.name := 'Larry Knight'
!busdriver3.dateOfBirth := Date('1975-02-02')
!busdriver3.phoneNumber := '555-9090'
!busdriver3.driverLicenseNr := 'DL789101'
!insert (reservation6, busdriver3) into BanquetBusDriver
!new ItemOrder('itemOrder4')
!itemOrder4.time := Time('20:45')
!insert (reservation5, itemOrder4) into ReservationItemOrdered
!new MenuItem('menuItem4')
!menuItem4.description := 'Spicy Thai Curry'
!menuItem4.prepTime := 30.0
!menuItem4.classification := #Main
!insert (itemOrder4, menuItem4) into ItemOrderMenuItem
!new FoodItem('foodItem4')
!foodItem4.number := 104
!foodItem4.description := 'Chili Peppers'
!foodItem4.purchaseFlag := true
!foodItem4.unit := #Pound
!insert (menuItem4, foodItem4) into MenuItemFoodItem
!new Allergen('allergen4')
!allergen4.type := #Lactose
!insert (foodItem4, allergen4) into FoodItemAllergen
!new Cook('cook4')
!cook4.name := 'Mason Green'
!cook4.dateOfBirth := Date('1988-11-16')
!cook4.phoneNumber := '555-3344'
!cook4.yearsOfExperience := 6
!new Chef('chef4')
!chef4.name := 'Ella Fitzgerald'
!chef4.dateOfBirth := Date('1984-07-23')
!chef4.phoneNumber := '555-5566'
!insert (menuItem4, chef4) into MenuItemChef
!insert (chef4, cook4) 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('restaurant4')
!restaurant4.name := 'Spice Symphony'
!new Owner('owner8')
!owner8.name := 'Nina Simone'
!owner8.percentageShares := 50
!insert (restaurant4, owner8) into RestaurantOwner
!new Owner('owner9')
!owner9.name := 'Henry Lee'
!owner9.percentageShares := 50
!insert (restaurant4, owner9) into RestaurantOwner
!new Table('table8')
!table8.number := 8
!table8.description := 'Long family table'
!table8.capacity := 12
!new Table('table9')
!table9.number := 9
!table9.description := 'Intimate booth'
!table9.capacity := 4
!new Table('table10')
!table10.number := 10
!table10.description := 'Outdoor dining'
!table10.capacity := 16
!new RegularCustomer('customer5')
!customer5.name := 'Olivia Benson'
!customer5.prefferedLanguage := #Spanish
!new Waiter('waiter6')
!waiter6.name := 'Carlos Ruiz'
!waiter6.dateOfBirth := Date('1993-04-14')
!waiter6.phoneNumber := '555-9988'
!waiter6.spokenLanguage := #English
!new HeadWaiter('headwaiter4')
!headwaiter4.name := 'Samantha Brown'
!headwaiter4.dateOfBirth := Date('1981-09-20')
!headwaiter4.phoneNumber := '555-4433'
!insert (headwaiter4, waiter6) into HeadWaiterWaiter
!new Individual('reservation5')
!reservation5.time := Time('20:00')
!reservation5.date := Date('2023-12-24')
!reservation5.numberPeople := 2
!reservation5.name := 'Olivia Benson'
!reservation5.phoneNumber := '555-7766'
!reservation5.number := 5
!reservation5.seating := #Inside
!reservation5.smoking := #NonSmoking
!insert (restaurant4, reservation5) into RestaurantReservation
!insert (reservation5, customer5) into ReservationCustomer
!insert (reservation5, waiter6) into ReservationWaiter
!insert (reservation5, table9) into ReservationTable
!new Banquet('reservation6')
!reservation6.time := Time('19:00')
!reservation6.date := Date('2023-12-31')
!reservation6.numberPeople := 25
!reservation6.name := 'New Year Party'
!reservation6.phoneNumber := '555-4567'
!reservation6.number := 6
!reservation6.groupName := 'Celebration Group'
!reservation6.paymentMethod := #CreditCard
!reservation6.busService := true
!insert (restaurant4, reservation6) into RestaurantReservation
!insert (reservation6, table8) into ReservationTable
!insert (reservation6, table10) into ReservationTable
!insert (reservation6, waiter6) into ReservationWaiter
!new BusDriver('busdriver3')
!busdriver3.name := 'Larry Knight'
!busdriver3.dateOfBirth := Date('1975-02-02')
!busdriver3.phoneNumber := '555-9090'
!busdriver3.driverLicenseNr := 'DL789101'
!insert (reservation6, busdriver3) into BanquetBusDriver
!new ItemOrder('itemOrder4')
!itemOrder4.time := Time('20:45')
!insert (reservation5, itemOrder4) into ReservationItemOrdered
!new MenuItem('menuItem4')
!menuItem4.description := 'Spicy Thai Curry'
!menuItem4.prepTime := 30.0
!menuItem4.classification := #Main
!insert (itemOrder4, menuItem4) into ItemOrderMenuItem
!new FoodItem('foodItem4')
!foodItem4.number := 104
!foodItem4.description := 'Chili Peppers'
!foodItem4.purchaseFlag := true
!foodItem4.unit := #Pound
!insert (menuItem4, foodItem4) into MenuItemFoodItem
!new Allergen('allergen4')
!allergen4.type := #Lactose
!insert (foodItem4, allergen4) into FoodItemAllergen
!new Cook('cook4')
!cook4.name := 'Mason Green'
!cook4.dateOfBirth := Date('1988-11-16')
!cook4.phoneNumber := '555-3344'
!cook4.yearsOfExperience := 6
!new Chef('chef4')
!chef4.name := 'Ella Fitzgerald'
!chef4.dateOfBirth := Date('1984-07-23')
!chef4.phoneNumber := '555-5566'
!insert (menuItem4, chef4) into MenuItemChef
!insert (chef4, cook4) into ChefCook
</object_model> LLM as a Judge
The object model associates 'foodItem4' (Chili Peppers) with 'allergen4' (Lactose). This is biologically and culinarily impossible, naturally occurring chili peppers are vegetables and do not contain dairy or lactose.
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 | $0.11 |
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 | 89.3% |
| 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('restaurant20')
!restaurant20.name := 'Alpen Gourmet'
!new Owner('owner42')
!owner42.name := 'Hans Müller'
!owner42.percentageShares := 60
!new Owner('owner43')
!owner43.name := 'Emma Schneider'
!owner43.percentageShares := 40
!insert (restaurant20, owner42) into RestaurantOwner
!insert (restaurant20, owner43) into RestaurantOwner
!new Table('table51')
!table51.number := 1
!table51.description := 'Elegant round table with a view of the Alps.'
!table51.capacity := 4
!new Table('table52')
!table52.number := 2
!table52.description := 'Private booth with a vintage wine rack.'
!table52.capacity := 2
!new Table('table53')
!table53.number := 3
!table53.description := 'Luxurious long table in the main dining hall.'
!table53.capacity := 8
!new RegularCustomer('customer15')
!customer15.name := 'Franziska Haas'
!customer15.prefferedLanguage := #German
!new RegularCustomer('customer16')
!customer16.name := 'John Doe'
!customer16.prefferedLanguage := #English
!new Individual('individualReservation10')
!individualReservation10.date := Date('2024-01-18')
!individualReservation10.time := Time('18:45')
!individualReservation10.numberPeople := 1
!individualReservation10.name := 'Franziska Haas'
!individualReservation10.phoneNumber := '5555555555' -- Arbitrary phone number
!individualReservation10.seating := #Inside
!individualReservation10.smoking := #NonSmoking
!individualReservation10.number := 10
!insert (restaurant20, individualReservation10) into RestaurantReservation
!insert (individualReservation10, customer15) into ReservationCustomer
!insert (individualReservation10, table52) into ReservationTable
!new Banquet('banquet17')
!banquet17.date := Date('2024-01-18')
!banquet17.time := Time('20:00')
!banquet17.groupName := 'John Doe\'s Business Meeting'
!banquet17.numberPeople := 10
!banquet17.paymentMethod := #CreditCard
!insert (restaurant20, banquet17) into RestaurantReservation
!insert (banquet17, customer16) into ReservationCustomer
!insert (banquet17, table53) into ReservationTable
!insert (banquet17, table51) into ReservationTable
!new Waiter('waiter36')
!waiter36.name := 'Clara Vogt'
!waiter36.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter36.phoneNumber := '6666666666' -- Arbitrary phone number
!waiter36.spokenLanguage := #German
!new Waiter('waiter37')
!waiter37.name := 'Karl Weber'
!waiter37.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!waiter37.phoneNumber := '7777777777' -- Arbitrary phone number
!waiter37.spokenLanguage := #German
!insert (individualReservation10, waiter36) into ReservationWaiter
!insert (banquet17, waiter36) into ReservationWaiter
!insert (banquet17, waiter37) into ReservationWaiter
!new HeadWaiter('headwaiter15')
!headwaiter15.name := 'Anja Fischer'
!headwaiter15.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter15.phoneNumber := '8888888888' -- Arbitrary phone number
!insert (headwaiter15, waiter36) into HeadWaiterWaiter
!insert (headwaiter15, waiter37) into HeadWaiterWaiter
!new BusDriver('busdriver17')
!busdriver17.name := 'Lukas Meier'
!insert (banquet17, busdriver17) into BanquetBusDriver
!new Chef('chef21')
!chef21.name := 'Dietrich Jaeger'
!chef21.dateOfBirth := Date('1960-01-01') -- Arbitrary date of birth
!chef21.phoneNumber := '9999999999' -- Arbitrary phone number
!new Cook('cook25')
!cook25.name := 'Gustav Zimmermann'
!cook25.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook25.phoneNumber := '1010101010' -- Arbitrary phone number
!cook25.yearsOfExperience := 5
!insert (chef21, cook25) into ChefCook
!new MenuItem('menuitem28')
!menuitem28.description := 'Traditional Swiss dish with veal, mushrooms, and cream sauce.'
!menuitem28.prepTime := 60.0
!menuitem28.classification := #Main
!insert (menuitem28, chef21) into MenuItemChef
!new FoodItem('fooditem46')
!fooditem46.number := 46
!fooditem46.description := 'Veal'
!fooditem46.purchaseFlag := true
!fooditem46.unit := #Pound
!new FoodItem('fooditem47')
!fooditem47.number := 47
!fooditem47.description := 'Mushrooms'
!fooditem47.purchaseFlag := true
!fooditem47.unit := #Pound
!new FoodItem('fooditem48')
!fooditem48.number := 48
!fooditem48.description := 'Cream'
!fooditem48.purchaseFlag := true
!fooditem48.unit := #Ounce
!insert (menuitem28, fooditem46) into MenuItemFoodItem
!insert (menuitem28, fooditem47) into MenuItemFoodItem
!insert (menuitem28, fooditem48) into MenuItemFoodItem
!new MenuItem('menuitem29')
!menuitem29.description := 'Light meringue with fresh raspberries and cream.'
!menuitem29.prepTime := 30.0
!menuitem29.classification := #Dessert
!insert (menuitem29, chef21) into MenuItemChef
!new FoodItem('fooditem49')
!fooditem49.number := 49
!fooditem49.description := 'Meringue'
!fooditem49.purchaseFlag := true
!fooditem49.unit := #Gram
!new FoodItem('fooditem50')
!fooditem50.number := 50
!fooditem50.description := 'Raspberries'
!fooditem50.purchaseFlag := true
!fooditem50.unit := #Gram
!insert (menuitem29, fooditem49) into MenuItemFoodItem
!insert (menuitem29, fooditem50) into MenuItemFoodItem
!insert (menuitem29, fooditem48) into MenuItemFoodItem
!new Allergen('allergen17')
!allergen17.type := #Lactose
!insert (fooditem48, allergen17) into FoodItemAllergen 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 charming Swiss town of Lucerne, there's a renowned fine dining establishment called "Alpen Gourmet." This restaurant offers a luxurious dining experience with a focus on Swiss and European cuisines, attracting food connoisseurs from around the world.
**Restaurant Instance:**
- **Name:** Alpen Gourmet
**Owner Instances:**
- **Name:** Hans Müller
- **Shares:** 60%
- **Language:** German
- **Related Restaurant:** Alpen Gourmet
- **Name:** Emma Schneider
- **Shares:** 40%
- **Language:** German, French
- **Related Restaurant:** Alpen Gourmet
**Table Instances:**
- **Table 1**
- **Number:** R01
- **Description:** Elegant round table with a view of the Alps.
- **Capacity:** 4
- **Table 2**
- **Number:** B12
- **Description:** Private booth with a vintage wine rack.
- **Capacity:** 2
- **Table 3**
- **Number:** T20
- **Description:** Luxurious long table in the main dining hall.
- **Capacity:** 8
**Regular Customer Instances:**
- **Name:** Franziska Haas
- **Preferred Language:** German
- **Reservation Type:** Individual Reservation
- Associated with Alpen Gourmet
- **Name:** John Doe
- **Preferred Language:** English
- **Reservation Type:** Banquet Reservation
- Associated with Alpen Gourmet
**Reservation Instances:**
- **Individual Reservation for Franziska Haas**
- **Date:** 2024-01-18
- **Time:** 18:45
- **Seating Preference:** Inside
- **Smoking Preference:** NonSmoking
- **Assigned Table:** Table B12 (Capacity 2)
- **Associated Waiter:** Clara Vogt
- **Banquet Reservation for John Doe's Business Meeting**
- **Date:** 2024-01-18
- **Time:** 20:00
- **Number of People:** 10
- **Payment Method:** CreditCard
- **Assigned Tables:** Table T20 (Capacity 8) and Table R01 (Capacity 4)
- **Bus Driver:** Lukas Meier
- **Associated Waiters:** Clara Vogt and Karl Weber
**Waiter Instances:**
- **Name:** Clara Vogt
- **Languages Spoken:** German, English
- **Experience:** 10 years
- Associated with Alpen Gourmet and both Reservations
- **Name:** Karl Weber
- **Languages Spoken:** German, French
- **Experience:** 7 years
- Associated with Alpen Gourmet and Banquet Reservation
**Head Waiter Instance:**
- **Name:** Anja Fischer
- **Languages Spoken:** German, Italian
- **Experience:** 12 years
- **Responsible for:** Clara Vogt and Karl Weber
**Bus Driver Instance:**
- **Name:** Lukas Meier
- **Experience:** 6 years
- Associated with John's Banquet
**Chef Instance:**
- **Name:** Dietrich Jaeger
- **Languages Spoken:** German, French, English
- **Experience:** 25 years
- **Supervises Cooks:** Gustav Zimmermann
**Cook Instance:**
- **Name:** Gustav Zimmermann
- **Languages Spoken:** German
- **Experience:** 5 years
- Supervised by Dietrich Jaeger
**MenuItem Instances:**
- **Veal Zürcher Geschnetzeltes**
- **Description:** Traditional Swiss dish with veal, mushrooms, and cream sauce.
- **Preparation Time:** 60 minutes
- **Classification:** Main
- **Designed by Chef:** Dietrich Jaeger
- **Food Items Used:** Veal, Mushrooms, Cream
- **Raspberry Meringue Delight**
- **Description:** Light meringue with fresh raspberries and cream.
- **Preparation Time:** 30 minutes
- **Classification:** Dessert
- **Designed by Chef:** Dietrich Jaeger
- **Food Items Used:** Meringue, Raspberries, Cream
**FoodItem Instances:**
- **Veal**
- **Unit:** Pound
- **Purchase:** True
- **Allergens:** None
- **Mushrooms**
- **Unit:** Pound
- **Purchase:** True
- **Allergens:** None
- **Cream**
- **Unit:** Ounce
- **Purchase:** True
- **Allergens:** Lactose
**Allergen Instances:**
- **Lactose**
- Associated with Food Item: Cream
This unique scenario at "Alpen Gourmet" captures the sophistication and elegance of fine dining, incorporating Swiss traditions with modern culinary trends. It demonstrates a well-rounded operational framework consistent with the conceptual model. The last output is partially incorrect:
temp.soil> !new Table('table51')
temp.soil> !table51.number := 'R01'
<input>:1:0: Type mismatch in assignment expression. Expected type `Integer', found `String'.
temp.soil> !new Table('table52')
temp.soil> !table52.number := 'B12'
<input>:1:0: Type mismatch in assignment expression. Expected type `Integer', found `String'.
temp.soil> !new Table('table53')
temp.soil> !table53.number := 'T20'
<input>:1:0: Type mismatch in assignment expression. Expected type `Integer', found `String'.
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('restaurant20')
!restaurant20.name := 'Alpen Gourmet'
!new Owner('owner42')
!owner42.name := 'Hans Müller'
!owner42.percentageShares := 60
!new Owner('owner43')
!owner43.name := 'Emma Schneider'
!owner43.percentageShares := 40
!insert (restaurant20, owner42) into RestaurantOwner
!insert (restaurant20, owner43) into RestaurantOwner
!new Table('table51')
!table51.number := 1
!table51.description := 'Elegant round table with a view of the Alps.'
!table51.capacity := 4
!new Table('table52')
!table52.number := 2
!table52.description := 'Private booth with a vintage wine rack.'
!table52.capacity := 2
!new Table('table53')
!table53.number := 3
!table53.description := 'Luxurious long table in the main dining hall.'
!table53.capacity := 8
!new RegularCustomer('customer15')
!customer15.name := 'Franziska Haas'
!customer15.prefferedLanguage := #German
!new RegularCustomer('customer16')
!customer16.name := 'John Doe'
!customer16.prefferedLanguage := #English
!new Individual('individualReservation10')
!individualReservation10.date := Date('2024-01-18')
!individualReservation10.time := Time('18:45')
!individualReservation10.numberPeople := 1
!individualReservation10.name := 'Franziska Haas'
!individualReservation10.phoneNumber := '5555555555' -- Arbitrary phone number
!individualReservation10.seating := #Inside
!individualReservation10.smoking := #NonSmoking
!individualReservation10.number := 10
!insert (restaurant20, individualReservation10) into RestaurantReservation
!insert (individualReservation10, customer15) into ReservationCustomer
!insert (individualReservation10, table52) into ReservationTable
!new Banquet('banquet17')
!banquet17.date := Date('2024-01-18')
!banquet17.time := Time('20:00')
!banquet17.groupName := 'John Doe\'s Business Meeting'
!banquet17.numberPeople := 10
!banquet17.paymentMethod := #CreditCard
!insert (restaurant20, banquet17) into RestaurantReservation
!insert (banquet17, customer16) into ReservationCustomer
!insert (banquet17, table53) into ReservationTable
!insert (banquet17, table51) into ReservationTable
!new Waiter('waiter36')
!waiter36.name := 'Clara Vogt'
!waiter36.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter36.phoneNumber := '6666666666' -- Arbitrary phone number
!waiter36.spokenLanguage := #German
!new Waiter('waiter37')
!waiter37.name := 'Karl Weber'
!waiter37.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!waiter37.phoneNumber := '7777777777' -- Arbitrary phone number
!waiter37.spokenLanguage := #German
!insert (individualReservation10, waiter36) into ReservationWaiter
!insert (banquet17, waiter36) into ReservationWaiter
!insert (banquet17, waiter37) into ReservationWaiter
!new HeadWaiter('headwaiter15')
!headwaiter15.name := 'Anja Fischer'
!headwaiter15.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter15.phoneNumber := '8888888888' -- Arbitrary phone number
!insert (headwaiter15, waiter36) into HeadWaiterWaiter
!insert (headwaiter15, waiter37) into HeadWaiterWaiter
!new BusDriver('busdriver17')
!busdriver17.name := 'Lukas Meier'
!insert (banquet17, busdriver17) into BanquetBusDriver
!new Chef('chef21')
!chef21.name := 'Dietrich Jaeger'
!chef21.dateOfBirth := Date('1960-01-01') -- Arbitrary date of birth
!chef21.phoneNumber := '9999999999' -- Arbitrary phone number
!new Cook('cook25')
!cook25.name := 'Gustav Zimmermann'
!cook25.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!cook25.phoneNumber := '1010101010' -- Arbitrary phone number
!cook25.yearsOfExperience := 5
!insert (chef21, cook25) into ChefCook
!new MenuItem('menuitem28')
!menuitem28.description := 'Traditional Swiss dish with veal, mushrooms, and cream sauce.'
!menuitem28.prepTime := 60.0
!menuitem28.classification := #Main
!insert (menuitem28, chef21) into MenuItemChef
!new FoodItem('fooditem46')
!fooditem46.number := 46
!fooditem46.description := 'Veal'
!fooditem46.purchaseFlag := true
!fooditem46.unit := #Pound
!new FoodItem('fooditem47')
!fooditem47.number := 47
!fooditem47.description := 'Mushrooms'
!fooditem47.purchaseFlag := true
!fooditem47.unit := #Pound
!new FoodItem('fooditem48')
!fooditem48.number := 48
!fooditem48.description := 'Cream'
!fooditem48.purchaseFlag := true
!fooditem48.unit := #Ounce
!insert (menuitem28, fooditem46) into MenuItemFoodItem
!insert (menuitem28, fooditem47) into MenuItemFoodItem
!insert (menuitem28, fooditem48) into MenuItemFoodItem
!new MenuItem('menuitem29')
!menuitem29.description := 'Light meringue with fresh raspberries and cream.'
!menuitem29.prepTime := 30.0
!menuitem29.classification := #Dessert
!insert (menuitem29, chef21) into MenuItemChef
!new FoodItem('fooditem49')
!fooditem49.number := 49
!fooditem49.description := 'Meringue'
!fooditem49.purchaseFlag := true
!fooditem49.unit := #Gram
!new FoodItem('fooditem50')
!fooditem50.number := 50
!fooditem50.description := 'Raspberries'
!fooditem50.purchaseFlag := true
!fooditem50.unit := #Gram
!insert (menuitem29, fooditem49) into MenuItemFoodItem
!insert (menuitem29, fooditem50) into MenuItemFoodItem
!insert (menuitem29, fooditem48) into MenuItemFoodItem
!new Allergen('allergen17')
!allergen17.type := #Lactose
!insert (fooditem48, allergen17) into FoodItemAllergen
</object_model> LLM as a Judge
The object model represents a highly plausible scenario. Restaurant ownership shares sum to exactly 100%, assigned table capacities comfortably accommodate the number of guests in both reservations, menu items are composed of logically appropriate ingredients with correct real-world allergens (Lactose for Cream), and all assigned staff and roles fit the operational real-world logic of a restaurant.
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 | $0.40 |
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 | 0/126 |
| 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 | 97.7% |
| String Equals | 99.8% |
| String LV | 90.7% |
| Shannon (Active) | 0.493 ± 0.494 |
| Shannon (All) | 0.276 ± 0.281 |
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 | 24/∞ |
| Attributes | 77/84 |
| Relationships | 25/∞ |
Viewer
!new Restaurant('restaurant19')
!restaurant19.name := 'Sunny Side Bistro'
!new Owner('owner39')
!owner39.name := 'Olga Ivanova'
!owner39.percentageShares := 20
!new Owner('owner40')
!owner40.name := 'Mateo Garcia'
!owner40.percentageShares := 30
!new Owner('owner41')
!owner41.name := 'Amneet Kaur'
!owner41.percentageShares := 50
!insert (restaurant19, owner39) into RestaurantOwner
!insert (restaurant19, owner40) into RestaurantOwner
!insert (restaurant19, owner41) into RestaurantOwner
!new RegularCustomer('customer14')
!customer14.name := 'Pierre Leblanc'
!customer14.prefferedLanguage := #English
!new HeadWaiter('headwaiter14')
!headwaiter14.name := 'Naomi Okafor'
!headwaiter14.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!headwaiter14.phoneNumber := '1111222233' -- Arbitrary phone number
!new Waiter('waiter35')
!waiter35.name := 'Ricardo Sousa'
!waiter35.dateOfBirth := Date('2000-01-01') -- Arbitrary date of birth
!waiter35.phoneNumber := '2222333344' -- Arbitrary phone number
!waiter35.spokenLanguage := #English
!insert (headwaiter14, waiter35) into HeadWaiterWaiter
!new Chef('chef20')
!chef20.name := 'Sophie Dupont'
!chef20.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!chef20.phoneNumber := '3333444455' -- Arbitrary phone number
!new Cook('cook24')
!cook24.name := 'Juanito Cruz'
!cook24.dateOfBirth := Date('2002-01-01') -- Arbitrary date of birth
!cook24.phoneNumber := '4444555566' -- Arbitrary phone number
!cook24.yearsOfExperience := 0
!insert (chef20, cook24) into ChefCook
!new BusDriver('busdriver16')
!busdriver16.name := 'Alice Jensen'
!new Table('table50')
!table50.number := 5
!table50.description := 'Outdoor garden view'
!table50.capacity := 4
!new MenuItem('menuitem27')
!menuitem27.description := 'A vibrant plate of mixed grilled vegetables and quinoa.'
!menuitem27.prepTime := 20.0
!menuitem27.classification := #Main
!insert (menuitem27, chef20) into MenuItemChef
!new FoodItem('fooditem45')
!fooditem45.number := 45
!fooditem45.description := 'Quinoa'
!fooditem45.purchaseFlag := true
!fooditem45.unit := #Gram
!insert (menuitem27, fooditem45) into MenuItemFoodItem
!new Allergen('allergen16')
!allergen16.type := #Nuts
!insert (fooditem45, allergen16) into FoodItemAllergen
!new Banquet('banquet16')
!banquet16.date := Date('2023-12-20')
!banquet16.time := Time('18:30')
!banquet16.groupName := 'Annual Family Gathering'
!banquet16.numberPeople := 4
!banquet16.paymentMethod := #Cash
!insert (restaurant19, banquet16) into RestaurantReservation
!insert (banquet16, table50) into ReservationTable
!insert (banquet16, waiter35) into ReservationWaiter
!insert (banquet16, busdriver16) into BanquetBusDriver
!new ItemOrder('itemorder4')
!itemorder4.time := Time('18:45')
!insert (banquet16, itemorder4) into ReservationItemOrdered
!insert (itemorder4, menuitem27) 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**: "Sunny Side Bistro"
### Owners
1. **Owner 1**:
- Name: Olga Ivanova
- Percentage Shares: 20%
2. **Owner 2**:
- Name: Mateo Garcia
- Percentage Shares: 30%
3. **Owner 3**:
- Name: Amneet Kaur
- Percentage Shares: 50%
### Regular Customers
- **Regular Customer**:
- Name: Pierre Leblanc
- Preferred Language: French
### Workers
1. **Head Waiter**:
- Name: Naomi Okafor
- Years of Experience: 10
- Languages Spoken: English, Igbo, French
2. **Waiters**:
- Name: Ricardo Sousa
- Years of Experience: 1
- Languages Spoken: English, Portuguese
- Head Waiter: Naomi Okafor
3. **Chefs**:
- Name: Sophie Dupont
- Years of Experience: 8
- Languages Spoken: English, French
4. **Cooks**:
- Name: Juanito Cruz
- Years of Experience: 0 (Minimum)
5. **Bus Driver**:
- Name: Alice Jensen
- Experience Years: 5
### Tables
1. **Table 1**:
- Number: 5
- Description: "Outdoor garden view"
- Capacity: 4
### Menu Items
1. **Menu Item**:
- Name: "Mediterranean Vegan Delight"
- Description: "A vibrant plate of mixed grilled vegetables and quinoa."
- Preparation Time: 20 minutes
- Classifications: Main
- Designer: Sophie Dupont
### Food Items
1. **Food Item**:
- Name: "Quinoa"
- Unit: Gram
- Purchase Flag: True
### Allergens
1. **Allergen**:
- Allergen Type: Nuts
### Reservations
1. **Reservation (Banquet)**:
- Reservation Date: "2023-12-20"
- Reservation Time: "18:30"
- Group Name: "Annual Family Gathering"
- Payment Method: Cash
- Assigned Tables: Table 1
- Number of People: 4 (Testing minimal number for banquet but utilizing full table capacity)
- Serving Waiter: Ricardo Sousa
- Bus Driver: Alice Jensen
### Item Orders
1. **Item Order 1**:
- Time Ordered: "18:45"
- Associated Reservation: Banquet Reservation for "Annual Family Gathering"
- Ordered Menu Item: Mediterranean Vegan Delight
### Relationships
- The ownership of "Sunny Side Bistro" is shared among Olga Ivanova, Mateo Garcia, and Amneet Kaur with precise shares adding up to 100%, adhering to the TotalOwnerShares constraint.
- Regular customer Pierre Leblanc appreciates service in French, reflecting the multilingual capabilities of staff under Naomi Okafor’s guidance.
- Ricardo Sousa, though the least experienced waiter, plays a pivotal role in small banquets, supported by language versatility for patron satisfaction.
- Chef Sophie Dupont’s cuisine reflects a healthy lifestyle with the "Mediterranean Vegan Delight", addressing allergy concerns of nuts in collaboration with novice cook Juanito Cruz.
- The table setup aligns with the minimal banquet capacity using a garden-facing setting to create intimate but vibrant gatherings.
- Alice Jensen facilitates group transport efficiently as a seasoned bus driver mitigating logistical challenges in event management.
This instance captures a proficiently managed banquet within seating constraints, focusing on cultural and dietary diversity, while maintaining structural and ownership integrity in a unique restaurant harmonizing different cultures. The last output is partially incorrect:
temp.soil> !customer14.name := 'Pierre Leblanc'
temp.soil> !customer14.prefferedLanguage := #French
<input>:1:0: generation of expression `#French' failed, with following error:
<input>:1:33: Undefined enumeration literal `French'.
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('restaurant19')
!restaurant19.name := 'Sunny Side Bistro'
!new Owner('owner39')
!owner39.name := 'Olga Ivanova'
!owner39.percentageShares := 20
!new Owner('owner40')
!owner40.name := 'Mateo Garcia'
!owner40.percentageShares := 30
!new Owner('owner41')
!owner41.name := 'Amneet Kaur'
!owner41.percentageShares := 50
!insert (restaurant19, owner39) into RestaurantOwner
!insert (restaurant19, owner40) into RestaurantOwner
!insert (restaurant19, owner41) into RestaurantOwner
!new RegularCustomer('customer14')
!customer14.name := 'Pierre Leblanc'
!customer14.prefferedLanguage := #English
!new HeadWaiter('headwaiter14')
!headwaiter14.name := 'Naomi Okafor'
!headwaiter14.dateOfBirth := Date('1983-01-01') -- Arbitrary date of birth
!headwaiter14.phoneNumber := '1111222233' -- Arbitrary phone number
!new Waiter('waiter35')
!waiter35.name := 'Ricardo Sousa'
!waiter35.dateOfBirth := Date('2000-01-01') -- Arbitrary date of birth
!waiter35.phoneNumber := '2222333344' -- Arbitrary phone number
!waiter35.spokenLanguage := #English
!insert (headwaiter14, waiter35) into HeadWaiterWaiter
!new Chef('chef20')
!chef20.name := 'Sophie Dupont'
!chef20.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!chef20.phoneNumber := '3333444455' -- Arbitrary phone number
!new Cook('cook24')
!cook24.name := 'Juanito Cruz'
!cook24.dateOfBirth := Date('2002-01-01') -- Arbitrary date of birth
!cook24.phoneNumber := '4444555566' -- Arbitrary phone number
!cook24.yearsOfExperience := 0
!insert (chef20, cook24) into ChefCook
!new BusDriver('busdriver16')
!busdriver16.name := 'Alice Jensen'
!new Table('table50')
!table50.number := 5
!table50.description := 'Outdoor garden view'
!table50.capacity := 4
!new MenuItem('menuitem27')
!menuitem27.description := 'A vibrant plate of mixed grilled vegetables and quinoa.'
!menuitem27.prepTime := 20.0
!menuitem27.classification := #Main
!insert (menuitem27, chef20) into MenuItemChef
!new FoodItem('fooditem45')
!fooditem45.number := 45
!fooditem45.description := 'Quinoa'
!fooditem45.purchaseFlag := true
!fooditem45.unit := #Gram
!insert (menuitem27, fooditem45) into MenuItemFoodItem
!new Allergen('allergen16')
!allergen16.type := #Nuts
!insert (fooditem45, allergen16) into FoodItemAllergen
!new Banquet('banquet16')
!banquet16.date := Date('2023-12-20')
!banquet16.time := Time('18:30')
!banquet16.groupName := 'Annual Family Gathering'
!banquet16.numberPeople := 4
!banquet16.paymentMethod := #Cash
!insert (restaurant19, banquet16) into RestaurantReservation
!insert (banquet16, table50) into ReservationTable
!insert (banquet16, waiter35) into ReservationWaiter
!insert (banquet16, busdriver16) into BanquetBusDriver
!new ItemOrder('itemorder4')
!itemorder4.time := Time('18:45')
!insert (banquet16, itemorder4) into ReservationItemOrdered
!insert (itemorder4, menuitem27) into ItemOrderMenuItem
</object_model> LLM as a Judge
The object model respects all domain constraints, such as the total owner shares equaling 100% and table capacity accommodating the number of guests. The chronological progression of events (reservation at 18:30, item order at 18:45) makes logical sense, and the ages/experience levels of the workers are practically sound. Having a bus driver for a small banquet of 4 people is slightly unusual but entirely plausible as a private shuttle service.
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 | $0.37 |
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 | 0/71 |
| 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 | 94.4% |
| String Equals | 100.0% |
| String LV | 90.9% |
| 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 | 73.7% |
| Attributes | 63.8% |
| Relationships | 92.3% |
Uncovered Items 27
Show all 21 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 | 41/48 |
| Relationships | 14/∞ |
Viewer
!new Restaurant('restaurant18')
!restaurant18.name := 'La Taverne Artisanale'
!new Owner('owner37')
!owner37.name := 'Clare O\'Sullivan'
!owner37.percentageShares := 50
!new Owner('owner38')
!owner38.name := 'Giovanni Testa'
!owner38.percentageShares := 50
!insert (restaurant18, owner37) into RestaurantOwner
!insert (restaurant18, owner38) into RestaurantOwner
!new Chef('chef19')
!chef19.name := 'Hans Kübler'
!chef19.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef19.phoneNumber := '5551112222' -- Arbitrary phone number
!new Cook('cook22')
!cook22.name := 'Julia Martinez'
!cook22.dateOfBirth := Date('1986-01-01') -- Arbitrary date of birth
!cook22.phoneNumber := '1234123412' -- Arbitrary phone number
!cook22.yearsOfExperience := 7
!new Cook('cook23')
!cook23.name := 'Shu Lin'
!cook23.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook23.phoneNumber := '4321432143' -- Arbitrary phone number
!cook23.yearsOfExperience := 4
!insert (chef19, cook22) into ChefCook
!insert (chef19, cook23) into ChefCook
!new Banquet('banquet15')
!banquet15.date := Date('2023-04-20')
!banquet15.time := Time('13:00')
!banquet15.groupName := 'European History Conference Luncheon'
!banquet15.numberPeople := 30
!banquet15.paymentMethod := #CreditCard
!insert (restaurant18, banquet15) into RestaurantReservation
!new Table('table47')
!table47.number := 20
!table47.description := 'Upper level with skyline view'
!table47.capacity := 25
!new Table('table48')
!table48.number := 21
!table48.description := 'Adjacent for collaborative activities'
!table48.capacity := 12
!insert (banquet15, table47) into ReservationTable
!insert (banquet15, table48) into ReservationTable
!new BusDriver('busdriver15')
!busdriver15.name := 'Antoni Chmielewski'
!insert (banquet15, busdriver15) into BanquetBusDriver
!new HeadWaiter('headwaiter13')
!headwaiter13.name := 'Laura Varga'
!headwaiter13.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!headwaiter13.phoneNumber := '5553334444' -- Arbitrary phone number
!new Waiter('waiter32')
!waiter32.name := 'Ahmed Rahman'
!waiter32.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!waiter32.phoneNumber := '6667778888' -- Arbitrary phone number
!waiter32.spokenLanguage := #English
!new Waiter('waiter33')
!waiter33.name := 'Nina Smirnova'
!waiter33.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter33.phoneNumber := '7778889999' -- Arbitrary phone number
!waiter33.spokenLanguage := #English
!insert (headwaiter13, waiter32) into HeadWaiterWaiter
!insert (headwaiter13, waiter33) into HeadWaiterWaiter
!insert (banquet15, waiter32) into ReservationWaiter
!insert (banquet15, waiter33) into ReservationWaiter
!new Individual('individualReservation9')
!individualReservation9.date := Date('2023-04-20')
!individualReservation9.time := Time('14:30')
!individualReservation9.numberPeople := 1
!individualReservation9.name := 'Isabella Neri'
!individualReservation9.phoneNumber := '8884441111' -- Arbitrary phone number
!individualReservation9.seating := #Inside
!individualReservation9.smoking := #NonSmoking
!individualReservation9.number := 9
!insert (restaurant18, individualReservation9) into RestaurantReservation
!new Table('table49')
!table49.number := 14
!table49.description := 'Cozy corner with art decor'
!table49.capacity := 2
!insert (individualReservation9, table49) into ReservationTable
!new Waiter('waiter34')
!waiter34.name := 'Stefan Novak'
!waiter34.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter34.phoneNumber := '9992221111' -- Arbitrary phone number
!waiter34.spokenLanguage := #English
!insert (headwaiter13, waiter34) into HeadWaiterWaiter
!insert (individualReservation9, waiter34) into ReservationWaiter
!new MenuItem('menuitem25')
!menuitem25.description := 'Traditional French chicken dish slow-cooked in wine'
!menuitem25.prepTime := 90.0
!menuitem25.classification := #Main
!insert (menuitem25, chef19) into MenuItemChef
!new FoodItem('fooditem39')
!fooditem39.number := 39
!fooditem39.description := 'Free-Range Chicken'
!fooditem39.unit := #Pound
!new FoodItem('fooditem40')
!fooditem40.number := 40
!fooditem40.description := 'Burgundy Wine'
!fooditem40.unit := #Ounce
!new FoodItem('fooditem41')
!fooditem41.number := 41
!fooditem41.description := 'Pearl Onions'
!fooditem41.unit := #Gram
!insert (menuitem25, fooditem39) into MenuItemFoodItem
!insert (menuitem25, fooditem40) into MenuItemFoodItem
!insert (menuitem25, fooditem41) into MenuItemFoodItem
!new MenuItem('menuitem26')
!menuitem26.description := 'Sparkling elderflower drink with a hint of lime'
!menuitem26.prepTime := 5.0
!menuitem26.classification := #Beverage
!insert (menuitem26, chef19) into MenuItemChef
!new FoodItem('fooditem42')
!fooditem42.number := 42
!fooditem42.description := 'Elderflower Cordial'
!fooditem42.unit := #Ounce
!new FoodItem('fooditem43')
!fooditem43.number := 43
!fooditem43.description := 'Sparkling Water'
!fooditem43.unit := #Ounce
!new FoodItem('fooditem44')
!fooditem44.number := 44
!fooditem44.description := 'Fresh Lime'
!fooditem44.unit := #Gram
!insert (menuitem26, fooditem42) into MenuItemFoodItem
!insert (menuitem26, fooditem43) into MenuItemFoodItem
!insert (menuitem26, fooditem44) into MenuItemFoodItem
!new RegularCustomer('customer13')
!customer13.name := 'Isabella Neri'
!customer13.prefferedLanguage := #Italian
!insert (individualReservation9, customer13) into ReservationCustomer 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: La Taverne Artisanale
### Restaurant: "La Taverne Artisanale"
- **Name:** La Taverne Artisanale
- **Owners:**
1. **Owner Name:** Clare O'Sullivan
- **Percentage Shares:** 50%
- **Languages Spoken:** English, Gaelic
2. **Owner Name:** Giovanni Testa
- **Percentage Shares:** 50%
- **Languages Spoken:** Italian, English
- **Menus:**
1. **Chef:** Hans Kübler
- **Languages Spoken:** German, French
- **Cook Team:**
- **Cook Name:** Julia Martinez
- **Years of Experience:** 7
- **Languages Spoken:** Spanish, English
- **Cook Name:** Shu Lin
- **Years of Experience:** 4
- **Languages Spoken:** Mandarin, English
### Reservations
1. **Reservation (Banquet):**
- **Date:** April 20, 2023
- **Time:** 13:00
- **Group Name:** European History Conference Luncheon
- **Payment Method:** CreditCard
- **Assigned BusDriver:** Antoni Chmielewski
- **Languages Spoken:** Polish, English
- **Assigned Tables:**
- **Table 1:**
- **Number:** 20
- **Description:** Upper level with skyline view
- **Capacity:** 25
- **Table 2:**
- **Number:** 21
- **Description:** Adjacent for collaborative activities
- **Capacity:** 12
- **Total Attendees:** 30
- **Assigned Waiters:**
- **HeadWaiter:** Laura Varga
- **Languages Spoken:** Hungarian, English
- **Waiters:**
- **Waiter Name:** Ahmed Rahman
- **Languages Spoken:** Arabic, French
- **Waiter Name:** Nina Smirnova
- **Languages Spoken:** Russian, English
2. **Reservation (Individual):**
- **Date:** April 20, 2023
- **Time:** 14:30
- **Customer Name:** Isabella Neri
- **Seating Preference:** Inside
- **Smoking Preference:** NonSmoking
- **Assigned Table:**
- **Number:** 14
- **Description:** Cozy corner with art decor
- **Capacity:** 2
- **Assigned Waiters:**
- **HeadWaiter:** Same as above
- **Waiter Name:** Stefan Novak
- **Languages Spoken:** Czech, English
### Menu Items
1. **Menu Item (Main): Coq au Vin**
- **Description:** Traditional French chicken dish slow-cooked in wine
- **Preparation Time:** 90 minutes
- **Chef:** Hans Kübler (as above)
- **Food Items:**
- **FoodItem 1:** Free-Range Chicken
- **Unit:** Pound
- **FoodItem 2:** Burgundy Wine
- **Unit:** Ounce
- **FoodItem 3:** Pearl Onions
- **Unit:** Gram
2. **Menu Item (Beverage): Elderflower Spritz**
- **Description:** Sparkling elderflower drink with a hint of lime
- **Preparation Time:** 5 minutes
- **Chef:** Hans Kübler (as above)
- **Food Items:**
- **FoodItem 1:** Elderflower Cordial
- **Unit:** Ounce
- **FoodItem 2:** Sparkling Water
- **Unit:** Ounce
- **FoodItem 3:** Fresh Lime
- **Unit:** Gram
- **Dietary Requirements:** Vegan
### Dietary Requirements
- **RegularCustomer:** Isabella Neri
- **Dietary Requirement:** Vegan
- **Preferred Language:** Italian
This instance features a French-themed restaurant with a focus on artisanal dining experiences and conferences. It presents a varied culinary team and an international staff, offering sophisticated dining options such as Coq au Vin and an exquisite Elderflower Spritz. La Taverne Artisanale caters to both individual patrons and conference attendees, showcasing its commitment to diverse culinary artistry and high-quality service. The last output is partially incorrect:
temp.soil>
temp.soil> !insert (fooditem44, diet11) into FoodItemDietaryRequirement
<input>:1:0: Association `FoodItemDietaryRequirement' does not exist.
temp.soil>
temp.soil> !insert (customer13, diet12) into ReportedAllergy
<input>:1:0: Association `ReportedAllergy' 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('restaurant18')
!restaurant18.name := 'La Taverne Artisanale'
!new Owner('owner37')
!owner37.name := 'Clare O\'Sullivan'
!owner37.percentageShares := 50
!new Owner('owner38')
!owner38.name := 'Giovanni Testa'
!owner38.percentageShares := 50
!insert (restaurant18, owner37) into RestaurantOwner
!insert (restaurant18, owner38) into RestaurantOwner
!new Chef('chef19')
!chef19.name := 'Hans Kübler'
!chef19.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef19.phoneNumber := '5551112222' -- Arbitrary phone number
!new Cook('cook22')
!cook22.name := 'Julia Martinez'
!cook22.dateOfBirth := Date('1986-01-01') -- Arbitrary date of birth
!cook22.phoneNumber := '1234123412' -- Arbitrary phone number
!cook22.yearsOfExperience := 7
!new Cook('cook23')
!cook23.name := 'Shu Lin'
!cook23.dateOfBirth := Date('1995-01-01') -- Arbitrary date of birth
!cook23.phoneNumber := '4321432143' -- Arbitrary phone number
!cook23.yearsOfExperience := 4
!insert (chef19, cook22) into ChefCook
!insert (chef19, cook23) into ChefCook
!new Banquet('banquet15')
!banquet15.date := Date('2023-04-20')
!banquet15.time := Time('13:00')
!banquet15.groupName := 'European History Conference Luncheon'
!banquet15.numberPeople := 30
!banquet15.paymentMethod := #CreditCard
!insert (restaurant18, banquet15) into RestaurantReservation
!new Table('table47')
!table47.number := 20
!table47.description := 'Upper level with skyline view'
!table47.capacity := 25
!new Table('table48')
!table48.number := 21
!table48.description := 'Adjacent for collaborative activities'
!table48.capacity := 12
!insert (banquet15, table47) into ReservationTable
!insert (banquet15, table48) into ReservationTable
!new BusDriver('busdriver15')
!busdriver15.name := 'Antoni Chmielewski'
!insert (banquet15, busdriver15) into BanquetBusDriver
!new HeadWaiter('headwaiter13')
!headwaiter13.name := 'Laura Varga'
!headwaiter13.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!headwaiter13.phoneNumber := '5553334444' -- Arbitrary phone number
!new Waiter('waiter32')
!waiter32.name := 'Ahmed Rahman'
!waiter32.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!waiter32.phoneNumber := '6667778888' -- Arbitrary phone number
!waiter32.spokenLanguage := #English
!new Waiter('waiter33')
!waiter33.name := 'Nina Smirnova'
!waiter33.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter33.phoneNumber := '7778889999' -- Arbitrary phone number
!waiter33.spokenLanguage := #English
!insert (headwaiter13, waiter32) into HeadWaiterWaiter
!insert (headwaiter13, waiter33) into HeadWaiterWaiter
!insert (banquet15, waiter32) into ReservationWaiter
!insert (banquet15, waiter33) into ReservationWaiter
!new Individual('individualReservation9')
!individualReservation9.date := Date('2023-04-20')
!individualReservation9.time := Time('14:30')
!individualReservation9.numberPeople := 1
!individualReservation9.name := 'Isabella Neri'
!individualReservation9.phoneNumber := '8884441111' -- Arbitrary phone number
!individualReservation9.seating := #Inside
!individualReservation9.smoking := #NonSmoking
!individualReservation9.number := 9
!insert (restaurant18, individualReservation9) into RestaurantReservation
!new Table('table49')
!table49.number := 14
!table49.description := 'Cozy corner with art decor'
!table49.capacity := 2
!insert (individualReservation9, table49) into ReservationTable
!new Waiter('waiter34')
!waiter34.name := 'Stefan Novak'
!waiter34.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter34.phoneNumber := '9992221111' -- Arbitrary phone number
!waiter34.spokenLanguage := #English
!insert (headwaiter13, waiter34) into HeadWaiterWaiter
!insert (individualReservation9, waiter34) into ReservationWaiter
!new MenuItem('menuitem25')
!menuitem25.description := 'Traditional French chicken dish slow-cooked in wine'
!menuitem25.prepTime := 90.0
!menuitem25.classification := #Main
!insert (menuitem25, chef19) into MenuItemChef
!new FoodItem('fooditem39')
!fooditem39.number := 39
!fooditem39.description := 'Free-Range Chicken'
!fooditem39.unit := #Pound
!new FoodItem('fooditem40')
!fooditem40.number := 40
!fooditem40.description := 'Burgundy Wine'
!fooditem40.unit := #Ounce
!new FoodItem('fooditem41')
!fooditem41.number := 41
!fooditem41.description := 'Pearl Onions'
!fooditem41.unit := #Gram
!insert (menuitem25, fooditem39) into MenuItemFoodItem
!insert (menuitem25, fooditem40) into MenuItemFoodItem
!insert (menuitem25, fooditem41) into MenuItemFoodItem
!new MenuItem('menuitem26')
!menuitem26.description := 'Sparkling elderflower drink with a hint of lime'
!menuitem26.prepTime := 5.0
!menuitem26.classification := #Beverage
!insert (menuitem26, chef19) into MenuItemChef
!new FoodItem('fooditem42')
!fooditem42.number := 42
!fooditem42.description := 'Elderflower Cordial'
!fooditem42.unit := #Ounce
!new FoodItem('fooditem43')
!fooditem43.number := 43
!fooditem43.description := 'Sparkling Water'
!fooditem43.unit := #Ounce
!new FoodItem('fooditem44')
!fooditem44.number := 44
!fooditem44.description := 'Fresh Lime'
!fooditem44.unit := #Gram
!insert (menuitem26, fooditem42) into MenuItemFoodItem
!insert (menuitem26, fooditem43) into MenuItemFoodItem
!insert (menuitem26, fooditem44) into MenuItemFoodItem
!new RegularCustomer('customer13')
!customer13.name := 'Isabella Neri'
!customer13.prefferedLanguage := #Italian
!insert (individualReservation9, customer13) into ReservationCustomer
</object_model> LLM as a Judge
The object model represents a plausible real-world restaurant scenario. The property values (prep times, table capacities, dates) are logical and physically possible. The relationship linkages properly map to real-world operations, such as assigning a sufficient number of table seats for reservations, appropriate ingredient units of measure, and correct ownership share distribution (summing to 100).
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 | $0.37 |
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 | 0/130 |
| 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 | 99.5% |
| String Equals | 99.8% |
| String LV | 90.3% |
| Shannon (Active) | 0.320 ± 0.453 |
| Shannon (All) | 0.188 ± 0.269 |
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 | 72.4% |
| Relationships | 76.9% |
Uncovered Items 25
Show all 16 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 | 80/93 |
| Relationships | 25/∞ |
Viewer
!new Restaurant('restaurant21')
!restaurant21.name := 'Simple Delights'
!new Owner('owner44')
!owner44.name := 'Rafael Nogueira'
!owner44.percentageShares := 60
!new Owner('owner45')
!owner45.name := 'Elise Fischer'
!owner45.percentageShares := 40
!insert (restaurant21, owner44) into RestaurantOwner
!insert (restaurant21, owner45) into RestaurantOwner
!new Individual('individualReservation11')
!individualReservation11.date := Date('2024-01-01')
!individualReservation11.time := Time('15:30')
!individualReservation11.numberPeople := 3
!individualReservation11.name := 'Emilia Watson'
!individualReservation11.phoneNumber := '5552223333' -- Arbitrary phone number
!individualReservation11.seating := #Inside
!individualReservation11.smoking := #NonSmoking
!individualReservation11.number := 11
!insert (restaurant21, individualReservation11) into RestaurantReservation
!new Table('table54')
!table54.number := 1
!table54.description := 'Cozy Corner'
!table54.capacity := 4
!insert (individualReservation11, table54) into ReservationTable
!new Waiter('waiter38')
!waiter38.name := 'Matteo Russo'
!waiter38.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter38.phoneNumber := '1112223334' -- Arbitrary phone number
!waiter38.spokenLanguage := #Spanish
!new HeadWaiter('headwaiter16')
!headwaiter16.name := 'Greta Müller'
!headwaiter16.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter16.phoneNumber := '2223334445' -- Arbitrary phone number
!insert (headwaiter16, waiter38) into HeadWaiterWaiter
!insert (individualReservation11, waiter38) into ReservationWaiter
!new Manager('manager4')
!manager4.name := 'Sonja Petrovic'
!manager4.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!manager4.phoneNumber := '3334445556' -- Arbitrary phone number
!new Chef('chef22')
!chef22.name := 'Anton Dubois'
!chef22.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef22.phoneNumber := '4445556667' -- Arbitrary phone number
!new Cook('cook26')
!cook26.name := 'Sophie Chan'
!cook26.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook26.phoneNumber := '5556667778' -- Arbitrary phone number
!cook26.yearsOfExperience := 5
!insert (chef22, cook26) into ChefCook
!new MenuItem('menuitem30')
!menuitem30.description := 'Fresh Avocado Salad'
!menuitem30.prepTime := 15.0
!menuitem30.classification := #Apetizer
!insert (menuitem30, chef22) into MenuItemChef
!new Chef('chef23')
!chef23.name := 'Jose Laporte'
!chef23.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef23.phoneNumber := '6667778889' -- Arbitrary phone number
!new Cook('cook27')
!cook27.name := 'Ahmed Omari'
!cook27.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!cook27.phoneNumber := '7778889990' -- Arbitrary phone number
!cook27.yearsOfExperience := 3
!insert (chef23, cook27) into ChefCook
!new MenuItem('menuitem31')
!menuitem31.description := 'Grilled Chicken Breasts'
!menuitem31.prepTime := 30.0
!menuitem31.classification := #Main
!insert (menuitem31, chef23) into MenuItemChef
!new Chef('chef24')
!chef24.name := 'Maria Bennett'
!chef24.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef24.phoneNumber := '8889990001' -- Arbitrary phone number
!new Cook('cook28')
!cook28.name := 'Nia Frazier'
!cook28.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!cook28.phoneNumber := '9990001112' -- Arbitrary phone number
!cook28.yearsOfExperience := 4
!insert (chef24, cook28) into ChefCook
!new MenuItem('menuitem32')
!menuitem32.description := 'Classic Apple Pie'
!menuitem32.prepTime := 40.0
!menuitem32.classification := #Dessert
!insert (menuitem32, chef24) into MenuItemChef
!new FoodItem('fooditem51')
!fooditem51.number := 51
!fooditem51.description := 'Pastry Dough'
!fooditem51.unit := #Pound
!fooditem51.purchaseFlag := true
!new FoodItem('fooditem52')
!fooditem52.number := 52
!fooditem52.description := 'Apples'
!fooditem52.unit := #Pound
!fooditem52.purchaseFlag := true
!new FoodItem('fooditem53')
!fooditem53.number := 53
!fooditem53.description := 'Cream'
!fooditem53.unit := #Ounce
!fooditem53.purchaseFlag := true
!insert (menuitem32, fooditem51) into MenuItemFoodItem
!insert (menuitem32, fooditem52) into MenuItemFoodItem
!insert (menuitem32, fooditem53) into MenuItemFoodItem
!new Allergen('allergen18')
!allergen18.type := #Gluten
!insert (fooditem51, allergen18) into FoodItemAllergen
!new Allergen('allergen19')
!allergen19.type := #Lactose
!insert (fooditem53, allergen19) into FoodItemAllergen
!new RegularCustomer('customer17')
!customer17.name := 'Emilia Watson'
!customer17.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:
**Instance: Minimalist `Walk-In` Dinner with Allergic Concerns**
### Description
This instance showcases an impromptu dinner scenario where a reservation emerges unexpectedly on a public holiday with a small group of guests, where one attendee has multiple severe allergies. This accentuates the system's capacity to handle immediate, complex dietary restrictions.
---
**Restaurant: Simple Delights**
- Name: Simple Delights
- Owners:
- **Owner1:** Rafael Nogueira, 60% shares
- **Owner2:** Elise Fischer, 40% shares
- Total shares: 100% (constraint met)
---
**Reservation: Impromptu Friends' Gathering**
- Type: Individual
- Date: 2024-01-01 (New Year's Day, emphasizing an unusual moment for a walk-in)
- Time: 15:30
- Customer: Emilia Watson
- Preferred Language: English
- Seating Preference: Inside
- Smoking Preference: NonSmoking
- Reserved for: 3 guests
---
**Table Assignments**
- **Table1:**
- Description: "Cozy Corner"
- Capacity: 4
- Total Capacity: 4 (meets constraint for seating)
---
**Personnel**
- **Waiters:**
- Matteo Russo (Language: Italian, Spanish)
- **HeadWaiter:** Greta Müller
- Manages one waiter, speaks German, English
- **Manager:** Sonja Petrovic
- Speaks Serbian, English
---
**Menu and Kitchen Staff**
- **MenuItems:**
- **Apetizer:** Fresh Avocado Salad
- Designed by Chef Anton Dubois
- Dietary: Vegetarian, Gluten-free
- Allergen: None
- **Main Dish:** Grilled Chicken Breasts
- Designed by Chef Jose Laporte
- Dietary: Kosher, Halal
- Allergen: None
- **Dessert:** Classic Apple Pie
- Designed by Chef Maria Bennett
- Dietary: Vegetarian
- Allergen: Gluten, Lactose
- **Cooks:**
- Cook under Anton Dubois: Sophie Chan (English)
- Cook under Jose Laporte: Ahmed Omari (Arabic)
- Cook under Maria Bennett: Nia Frazier (French)
- **Chefs Overseeing Items:**
- **Chef Anton Dubois**
- Supervises 1 Cook
- Languages: French, English
- **Chef Jose Laporte**
- Supervises 1 Cook
- Languages: Spanish, English
- **Chef Maria Bennett**
- Supervises 1 Cook
- Languages: English
- **Reported Allergies**:
- Regular Customer: Emilia Watson
- Allergies reported: Nuts, Seafood
---
### Uncommon Aspects:
- Occurrence of a small group walk-in reservation on New Year's Day, which is a time generally expected to be prepared only for preset reservations.
- Severe allergy considerations with specific dietary needs addressed within an impromptu setup, testing the restaurant's readiness and flexibility.
- Language diversity focuses on specific attendee needs, considering staff are there due to holiday rotations.
- Simple menu focused on dietary safety with an emphasis on rapid, safe preparation processes.
This instance explores a minimalist reservation configuration with heightened sensitivity to dietary and allergen concerns, combined with spontaneous attendance on a holiday, providing a unique edge case scenario. The last output is partially incorrect:
temp.soil>
temp.soil> !insert (menuitem32, allergen18) into MenuItemFoodItem
<input>:1:0: Participant 2 of association `MenuItemFoodItem' must be of type `FoodItem', but `allergen18' is of type `Allergen'.
temp.soil>
temp.soil> !insert (menuitem32, allergen19) into MenuItemFoodItem
<input>:1:0: Participant 2 of association `MenuItemFoodItem' must be of type `FoodItem', but `allergen19' is of type `Allergen'.
temp.soil>
temp.soil> !insert (customer17, allergy1) into ReportedAllergy
<input>:1:0: Association `ReportedAllergy' does not exist.
temp.soil> !insert (customer17, allergy2) into ReportedAllergy
<input>:1:0: Association `ReportedAllergy' 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('restaurant21')
!restaurant21.name := 'Simple Delights'
!new Owner('owner44')
!owner44.name := 'Rafael Nogueira'
!owner44.percentageShares := 60
!new Owner('owner45')
!owner45.name := 'Elise Fischer'
!owner45.percentageShares := 40
!insert (restaurant21, owner44) into RestaurantOwner
!insert (restaurant21, owner45) into RestaurantOwner
!new Individual('individualReservation11')
!individualReservation11.date := Date('2024-01-01')
!individualReservation11.time := Time('15:30')
!individualReservation11.numberPeople := 3
!individualReservation11.name := 'Emilia Watson'
!individualReservation11.phoneNumber := '5552223333' -- Arbitrary phone number
!individualReservation11.seating := #Inside
!individualReservation11.smoking := #NonSmoking
!individualReservation11.number := 11
!insert (restaurant21, individualReservation11) into RestaurantReservation
!new Table('table54')
!table54.number := 1
!table54.description := 'Cozy Corner'
!table54.capacity := 4
!insert (individualReservation11, table54) into ReservationTable
!new Waiter('waiter38')
!waiter38.name := 'Matteo Russo'
!waiter38.dateOfBirth := Date('1985-01-01') -- Arbitrary date of birth
!waiter38.phoneNumber := '1112223334' -- Arbitrary phone number
!waiter38.spokenLanguage := #Spanish
!new HeadWaiter('headwaiter16')
!headwaiter16.name := 'Greta Müller'
!headwaiter16.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!headwaiter16.phoneNumber := '2223334445' -- Arbitrary phone number
!insert (headwaiter16, waiter38) into HeadWaiterWaiter
!insert (individualReservation11, waiter38) into ReservationWaiter
!new Manager('manager4')
!manager4.name := 'Sonja Petrovic'
!manager4.dateOfBirth := Date('1975-01-01') -- Arbitrary date of birth
!manager4.phoneNumber := '3334445556' -- Arbitrary phone number
!new Chef('chef22')
!chef22.name := 'Anton Dubois'
!chef22.dateOfBirth := Date('1965-01-01') -- Arbitrary date of birth
!chef22.phoneNumber := '4445556667' -- Arbitrary phone number
!new Cook('cook26')
!cook26.name := 'Sophie Chan'
!cook26.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!cook26.phoneNumber := '5556667778' -- Arbitrary phone number
!cook26.yearsOfExperience := 5
!insert (chef22, cook26) into ChefCook
!new MenuItem('menuitem30')
!menuitem30.description := 'Fresh Avocado Salad'
!menuitem30.prepTime := 15.0
!menuitem30.classification := #Apetizer
!insert (menuitem30, chef22) into MenuItemChef
!new Chef('chef23')
!chef23.name := 'Jose Laporte'
!chef23.dateOfBirth := Date('1970-01-01') -- Arbitrary date of birth
!chef23.phoneNumber := '6667778889' -- Arbitrary phone number
!new Cook('cook27')
!cook27.name := 'Ahmed Omari'
!cook27.dateOfBirth := Date('1992-01-01') -- Arbitrary date of birth
!cook27.phoneNumber := '7778889990' -- Arbitrary phone number
!cook27.yearsOfExperience := 3
!insert (chef23, cook27) into ChefCook
!new MenuItem('menuitem31')
!menuitem31.description := 'Grilled Chicken Breasts'
!menuitem31.prepTime := 30.0
!menuitem31.classification := #Main
!insert (menuitem31, chef23) into MenuItemChef
!new Chef('chef24')
!chef24.name := 'Maria Bennett'
!chef24.dateOfBirth := Date('1980-01-01') -- Arbitrary date of birth
!chef24.phoneNumber := '8889990001' -- Arbitrary phone number
!new Cook('cook28')
!cook28.name := 'Nia Frazier'
!cook28.dateOfBirth := Date('1991-01-01') -- Arbitrary date of birth
!cook28.phoneNumber := '9990001112' -- Arbitrary phone number
!cook28.yearsOfExperience := 4
!insert (chef24, cook28) into ChefCook
!new MenuItem('menuitem32')
!menuitem32.description := 'Classic Apple Pie'
!menuitem32.prepTime := 40.0
!menuitem32.classification := #Dessert
!insert (menuitem32, chef24) into MenuItemChef
!new FoodItem('fooditem51')
!fooditem51.number := 51
!fooditem51.description := 'Pastry Dough'
!fooditem51.unit := #Pound
!fooditem51.purchaseFlag := true
!new FoodItem('fooditem52')
!fooditem52.number := 52
!fooditem52.description := 'Apples'
!fooditem52.unit := #Pound
!fooditem52.purchaseFlag := true
!new FoodItem('fooditem53')
!fooditem53.number := 53
!fooditem53.description := 'Cream'
!fooditem53.unit := #Ounce
!fooditem53.purchaseFlag := true
!insert (menuitem32, fooditem51) into MenuItemFoodItem
!insert (menuitem32, fooditem52) into MenuItemFoodItem
!insert (menuitem32, fooditem53) into MenuItemFoodItem
!new Allergen('allergen18')
!allergen18.type := #Gluten
!insert (fooditem51, allergen18) into FoodItemAllergen
!new Allergen('allergen19')
!allergen19.type := #Lactose
!insert (fooditem53, allergen19) into FoodItemAllergen
!new RegularCustomer('customer17')
!customer17.name := 'Emilia Watson'
!customer17.prefferedLanguage := #English
</object_model> LLM as a Judge
The object model is logically consistent with the domain. The attributes reflect sensible real-world values, such as valid adult ages for staff, appropriate preparation times for menu items (15-40 minutes), and table capacities that fit the party sizes. Additionally, the ingredients and allergens accurately match their menu items (e.g., Apple Pie containing dough with gluten and cream with lactose).
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 | $0.41 |
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 | 0/112 |
| Multiplicities | 0/17 |
| 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 | 97.1% |
| String Equals | 99.8% |
| String LV | 92.4% |
| Shannon (Active) | 0.486 ± 0.487 |
| Shannon (All) | 0.281 ± 0.305 |
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 | 70.7% |
| Relationships | 69.2% |
Uncovered Items 27
Show all 17 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 | 23/∞ |
| Attributes | 72/72 |
| Relationships | 17/∞ |
Viewer
!new Restaurant('restaurant14')
!restaurant14.name := 'The Artistic Plate'
!new Owner('owner28')
!owner28.name := 'Fatima El-Hassan'
!owner28.percentageShares := 50
!new Owner('owner29')
!owner29.name := 'Rafael Cortez'
!owner29.percentageShares := 50
!insert (restaurant14, owner28) into RestaurantOwner
!insert (restaurant14, owner29) into RestaurantOwner
!new Banquet('banquet11')
!banquet11.date := Date('2023-11-05')
!banquet11.time := Time('19:00')
!banquet11.groupName := 'Local Artists Collective'
!banquet11.numberPeople := 80
!banquet11.paymentMethod := #CreditCard
!insert (restaurant14, banquet11) into RestaurantReservation
!new Table('table36')
!table36.number := 401
!table36.description := 'Long exhibition table'
!table36.capacity := 20
!new Table('table37')
!table37.number := 402
!table37.description := 'Artistic round table'
!table37.capacity := 15
!new Table('table38')
!table38.number := 403
!table38.description := 'Square gallery table'
!table38.capacity := 10
!insert (banquet11, table36) into ReservationTable
!insert (banquet11, table37) into ReservationTable
!insert (banquet11, table38) into ReservationTable
!new BusDriver('busdriver11')
!busdriver11.name := 'Manoj Nair'
!insert (banquet11, busdriver11) into BanquetBusDriver
!new Waiter('waiter23')
!waiter23.name := 'Clara Fischer'
!waiter23.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter23.phoneNumber := '1231231234' -- Arbitrary phone number
!waiter23.spokenLanguage := #English
!new Waiter('waiter24')
!waiter24.name := 'Luis Alvarez'
!waiter24.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter24.phoneNumber := '2342342345' -- Arbitrary phone number
!waiter24.spokenLanguage := #English
!insert (banquet11, waiter23) into ReservationWaiter
!insert (banquet11, waiter24) 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: Community Art Gala at "The Artistic Plate"
### Entities:
1. **Restaurant:**
- Name: The Artistic Plate
2. **Owner:**
- Name: Fatima El-Hassan
- Percentage Shares: 50%
3. **Owner:**
- Name: Rafael Cortez
- Percentage Shares: 50%
4. **Banquet (Reservation):**
- Date: "2023-11-05"
- Time: "19:00"
- Group Name: Local Artists Collective
- Number of People: 80
- Payment Method: CreditCard
5. **Table (Assigned to Banquet):**
- Number: T401
- Description: Long exhibition table
- Capacity: 20
6. **Table (Assigned to Banquet):**
- Number: T402
- Description: Artistic round table
- Capacity: 15
7. **Table (Assigned to Banquet):**
- Number: T403
- Description: Square gallery table
- Capacity: 10
8. **BusDriver:**
- Name: Manoj Nair
- Language: Hindi, English
9. **Waiter:**
- Name: Clara Fischer
- Languages Spoken: German, English
- Years of Experience: 4
10. **Waiter:**
- Name: Luis Alvarez
- Languages Spoken: Spanish, English
- Years of Experience: 6
### Relationships:
1. **Restaurant-Owner (RestaurantOwner):**
- The Artistic Plate - Fatima El-Hassan
- The Artistic Plate - Rafael Cortez
2. **Restaurant-Reservation (RestaurantReservation):**
- The Artistic Plate - Local Artists Collective Banquet
3. **Banquet-BusDriver (BanquetBusDriver):**
- Local Artists Collective - Manoj Nair
4. **Reservation-Table (ReservationTable - Violates Constraint):**
- Local Artists Collective is assigned with T401, T402, T403
5. **Reservation-Waiter (ReservationWaiter - Violates Multiplicity):**
- Local Artists Collective Banquet served by Clara Fischer and Luis Alvarez
### Explanation of Overconstraint Detection:
This instance features a community art gala organized by the Local Artists Collective at The Artistic Plate. The banquet accommodates 80 guests but only has tables T401, T402, and T403, with a combined seating capacity of 45. This setup violates the 'TablesCapacityGreaterThanPeople' constraint that mandates sufficient seating for all attendees.
Additionally, only two waiters, Clara Fischer and Luis Alvarez, are assigned to serve, meeting the minimum requirement of one waiter but possibly being too few given the high number of attendees, which stresses the operational efficiency beyond the multiplicity rule while remaining within its definition. This scenario highlights the potential for logistical issues despite adhering to constraints, such as during special events with unique spatial arrangements or staffing challenges. <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('restaurant14')
!restaurant14.name := 'The Artistic Plate'
!new Owner('owner28')
!owner28.name := 'Fatima El-Hassan'
!owner28.percentageShares := 50
!new Owner('owner29')
!owner29.name := 'Rafael Cortez'
!owner29.percentageShares := 50
!insert (restaurant14, owner28) into RestaurantOwner
!insert (restaurant14, owner29) into RestaurantOwner
!new Banquet('banquet11')
!banquet11.date := Date('2023-11-05')
!banquet11.time := Time('19:00')
!banquet11.groupName := 'Local Artists Collective'
!banquet11.numberPeople := 80
!banquet11.paymentMethod := #CreditCard
!insert (restaurant14, banquet11) into RestaurantReservation
!new Table('table36')
!table36.number := 401
!table36.description := 'Long exhibition table'
!table36.capacity := 20
!new Table('table37')
!table37.number := 402
!table37.description := 'Artistic round table'
!table37.capacity := 15
!new Table('table38')
!table38.number := 403
!table38.description := 'Square gallery table'
!table38.capacity := 10
!insert (banquet11, table36) into ReservationTable
!insert (banquet11, table37) into ReservationTable
!insert (banquet11, table38) into ReservationTable
!new BusDriver('busdriver11')
!busdriver11.name := 'Manoj Nair'
!insert (banquet11, busdriver11) into BanquetBusDriver
!new Waiter('waiter23')
!waiter23.name := 'Clara Fischer'
!waiter23.dateOfBirth := Date('1990-01-01') -- Arbitrary date of birth
!waiter23.phoneNumber := '1231231234' -- Arbitrary phone number
!waiter23.spokenLanguage := #English
!new Waiter('waiter24')
!waiter24.name := 'Luis Alvarez'
!waiter24.dateOfBirth := Date('1987-01-01') -- Arbitrary date of birth
!waiter24.phoneNumber := '2342342345' -- Arbitrary phone number
!waiter24.spokenLanguage := #English
!insert (banquet11, waiter23) into ReservationWaiter
!insert (banquet11, waiter24) into ReservationWaiter
</object_model> LLM as a Judge
The total capacity of the tables assigned to the banquet ('table36' with 20, 'table37' with 15, and 'table38' with 10) equals 45, which is insufficient for the 80 people assigned to 'banquet11'. This violates basic physical constraints and the domain invariant `TablesCapacityGreaterThanPeople`.
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 | $0.16 |
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 | 0/47 |
| Multiplicities | 2/9 |
| 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 | 97.2% |
| String Equals | 100.0% |
| String LV | 86.3% |
| 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 | 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 | 10/∞ |
| Attributes | 28/35 |
| Relationships | 9/∞ |