Triple
T21628288
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vikas Khanna |
E533759
|
entity |
| Predicate | restaurantCuisine |
P59511
|
FINISHED |
| Object | Junoon, Indian 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: Junoon, Indian cuisine | Statement: [Vikas Khanna, restaurantCuisine, Junoon, Indian cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restaurantCuisine Context triple: [Vikas Khanna, restaurantCuisine, Junoon, Indian cuisine]
-
A.
restaurantContained
Indicates that a restaurant is physically located within or is a part of a larger place or establishment.
-
B.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
C.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
haveCuisine
chosen
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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5214e72c8190af109089f58fca4f |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:34 p.m.