Triple
T9496701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cravings: All Together |
E229024
|
entity |
| Predicate | hasCookingStyle |
P59511
|
FINISHED |
| Object | American cuisine–influenced dishes |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: American cuisine–influenced dishes | Statement: [Cravings: All Together, hasCookingStyle, American cuisine–influenced dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCookingStyle Context triple: [Cravings: All Together, hasCookingStyle, American cuisine–influenced dishes]
-
A.
foodPreparationStyle
Indicates the manner or method by which food is prepared, cooked, or processed.
-
B.
haveCuisine
chosen
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
C.
usesCookingMethod
Indicates that one entity prepares or processes another entity by applying a specific cooking technique or method.
-
D.
cuisineSubtype
Indicates that one cuisine is a more specific subtype or variant within the broader category of another cuisine.
-
E.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd95ecf4148190aa8f4733980166ae |
completed | April 1, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:56 p.m.