Triple
T27815939
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Biscuits n’ Gravy |
E702665
|
entity |
| Predicate | referencesCuisine |
P6863
|
FINISHED |
| Object | Southern United States cuisine |
—
|
NE NERFINISHED |
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: Southern United States cuisine | Statement: [Biscuits n’ Gravy, referencesCuisine, Southern United States cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: referencesCuisine Context triple: [Biscuits n’ Gravy, referencesCuisine, Southern United States cuisine]
-
A.
referencesDish
Indicates that one entity cites, mentions, or points to a specific dish as a reference.
-
B.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
-
C.
cuisine
chosen
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
D.
cuisineInfluence
Indicates that one cuisine has had a notable impact on the development, style, or characteristics of another cuisine.
-
E.
knownForDish
Indicates that an entity is recognized or notable for preparing, serving, or being associated with a particular 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_69ef840a16748190926719ab96120bae |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: April 27, 2026, 5:45 p.m.