Triple
T16662114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Seasons Restaurant |
E404883
|
entity |
| Predicate | MichelinStar |
P11848
|
FINISHED |
| Object | 1 star (various years) |
—
|
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: 1 star (various years) | Statement: [Four Seasons Restaurant, MichelinStar, 1 star (various years)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: MichelinStar Context triple: [Four Seasons Restaurant, MichelinStar, 1 star (various years)]
-
A.
hasMichelinStar
chosen
Indicates that a restaurant or dining establishment has been awarded at least one Michelin star for its culinary quality.
-
B.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
-
C.
rankInsigniaStars
Indicates the number or configuration of stars displayed on a rank insignia to denote a specific rank or level.
-
D.
starIs
Indicates that one entity is identified or classified as a star in relation to another entity or context.
-
E.
isThreeStarRank
Indicates that an entity holds or is assigned a three-star rank or rating within a defined ranking system.
- 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_69d8838b5fbc81908c6575c132b82e80 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37c99efa8819096c6325ff4898bd7 |
completed | April 18, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69e319b1d7f08190b5ecb4a68c636c15 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:18 a.m.