Triple
T28059358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinatown (Manhattan) |
E709059
|
entity |
| Predicate | majorEthnicCuisine |
P6863
|
FINISHED |
| Object | Chinese 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: Chinese cuisine | Statement: [Chinatown (Manhattan), majorEthnicCuisine, Chinese cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorEthnicCuisine Context triple: [Chinatown (Manhattan), majorEthnicCuisine, Chinese cuisine]
-
A.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
B.
cooksCuisine
Indicates that a person or agent prepares or specializes in making a particular type 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.
traditionalCuisine
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.
- 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_69ef9b6eb6d88190a3fea236eb0f7bed |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd2839880c819099a7a89783f2270e |
completed | May 8, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69fd23dc5da48190ae8ba08947d34956 |
completed | May 7, 2026, 11:44 p.m. |
Created at: April 27, 2026, 8:38 p.m.