Triple
T23271632
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Restaurant Gordon Ramsay |
E588305
|
entity |
| Predicate | hasMichelinStarCount |
P151628
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Restaurant Gordon Ramsay, hasMichelinStarCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMichelinStarCount Context triple: [Restaurant Gordon Ramsay, hasMichelinStarCount, 3]
-
A.
hasMichelinStar
Indicates that a restaurant or dining establishment has been awarded at least one Michelin star for its culinary quality.
-
B.
estimatedStarCount
Indicates the approximate number of stars that are believed or calculated to exist in or be associated with a given astronomical object or region.
-
C.
numberOfRevolvingRestaurants
Indicates the quantity of revolving restaurants associated with or contained within a given entity.
-
D.
hasNumberOfRestaurantsAndBars
Indicates the total count of restaurants and bars associated with a given entity.
-
E.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
- F. None of above. chosen
Provenance (4 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1957418fc819085ee528622e0c6de |
completed | April 29, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69effcecabd88190856fb6e1d993e4dd |
completed | April 28, 2026, 12:18 a.m. |
| PDg | Predicate description generation | batch_69f01d8770d081908897c28b04e5faea |
completed | April 28, 2026, 2:37 a.m. |
Created at: April 17, 2026, 4:46 p.m.