Triple
T23760265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nine-turn Large Intestine |
E587229
|
entity |
| Predicate | regionalCuisineOf |
P5786
|
FINISHED |
| Object | Northern China |
—
|
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: Northern China | Statement: [Nine-turn Large Intestine, regionalCuisineOf, Northern China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalCuisineOf Context triple: [Nine-turn Large Intestine, regionalCuisineOf, Northern China]
-
A.
cuisineType
chosen
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
B.
isNationalDishOf
Indicates that a particular food is officially or culturally recognized as the national dish of a specific country or region.
-
C.
includesRegionalCuisine
Indicates that one entity incorporates or features the regional cuisine associated with another entity.
-
D.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
E.
ethnicRegionalBase
Indicates that an entity’s support, identity, or operations are primarily rooted in a specific ethnic group within a particular geographic region.
- 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_69e2490b8ac48190a6b35f1d5500486b |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bdb1d6348190afb3f0fbea1b9ca3 |
completed | April 29, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69f155f79e34819080f9ddb972b34deb |
completed | April 29, 2026, 12:51 a.m. |
Created at: April 17, 2026, 7:14 p.m.