Triple
T24252828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Cromwell Las Vegas |
E603578
|
entity |
| Predicate | hasCelebrityChefRestaurant |
P4442
|
FINISHED |
| Object | Giada – The Restaurant |
—
|
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: Giada – The Restaurant | Statement: [The Cromwell Las Vegas, hasCelebrityChefRestaurant, Giada – The Restaurant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCelebrityChefRestaurant Context triple: [The Cromwell Las Vegas, hasCelebrityChefRestaurant, Giada – The Restaurant]
-
A.
hasRestaurant
chosen
Indicates that one entity possesses, operates, or contains a restaurant associated with it.
-
B.
hasRestaurantType
Indicates that an entity is associated with or classified as a particular type or category of restaurant.
-
C.
hasFictionalDiner
Indicates that one entity features or includes a fictional diner associated with another entity.
-
D.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
E.
hasMichelinStar
Indicates that a restaurant or dining establishment has been awarded at least one Michelin star for its culinary quality.
- 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_69e29540da0481909a38bdae315b7a02 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f28b8aff788190bb37fc8ab04bde00 |
completed | April 29, 2026, 10:51 p.m. |
| PD | Predicate disambiguation | batch_69f1c450aa508190bc9d372a5f6ee47a |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 18, 2026, 12:05 a.m.