Triple
T4303066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Village West |
E99885
|
entity |
| Predicate | hasRestaurantCluster |
P40355
|
FINISHED |
| Object | Village West restaurants |
—
|
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: Village West restaurants | Statement: [Village West, hasRestaurantCluster, Village West restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRestaurantCluster Context triple: [Village West, hasRestaurantCluster, Village West restaurants]
-
A.
hasRestaurant
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
B.
hasRestaurantsAndCafes
chosen
Indicates that the subject location contains or provides access to restaurants and cafés.
-
C.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
numberOfRestaurants
Indicates the quantitative count of restaurants associated with a given entity or context.
- 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_69b345528ebc8190b5abc7e95094792d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350b792608190ac778b79c740256a |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b347ff45cc8190b0cc335a94cc3d73 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:08 p.m.