Triple
T23760272
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nine-turn Large Intestine |
E587229
|
entity |
| Predicate | associatedCuisineStyle |
P5786
|
FINISHED |
| Object | classic Lu 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: classic Lu cuisine | Statement: [Nine-turn Large Intestine, associatedCuisineStyle, classic Lu cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCuisineStyle Context triple: [Nine-turn Large Intestine, associatedCuisineStyle, classic Lu cuisine]
-
A.
foodPreparationStyle
Indicates the manner or method by which food is prepared, cooked, or processed.
-
B.
cuisineType
chosen
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
C.
cuisineSubtype
Indicates that one cuisine is a more specific subtype or variant within the broader category of another cuisine.
-
D.
sharesCuisineWith
Indicates that two entities offer or are associated with the same type or style of cuisine.
-
E.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
- 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.