Triple
T191736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern United States |
E3735
|
entity |
| Predicate | hasCuisine |
P1016
|
FINISHED |
| Object | Southern cuisine |
—
|
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: Southern cuisine | Statement: [Southern United States, hasCuisine, Southern cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCuisine Context triple: [Southern United States, hasCuisine, Southern cuisine]
-
A.
traditionalCuisine
chosen
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
B.
hasCulturalFeature
Indicates that an entity possesses, includes, or is characterized by a particular cultural element, attribute, or landmark.
-
C.
placeOfOrigin
Indicates the location or source from which an entity originally comes or was created.
-
D.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
E.
countryOfOrigin
Indicates the country from which an entity originally comes or was first produced, created, or established.
- 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_69a2548debd48190ae3a06d6e65b53c6 |
completed | Feb. 28, 2026, 2:35 a.m. |
| NER | Named-entity recognition | batch_69a25964fc5c8190bd3e37daaf695ecf |
completed | Feb. 28, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69a2567567508190b3a41329a15c7156 |
completed | Feb. 28, 2026, 2:44 a.m. |
Created at: Feb. 28, 2026, 2:41 a.m.