Triple
T268382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ristorante Caterina de’ Medici |
E5782
|
entity |
| Predicate | diningStyle |
P9631
|
FINISHED |
| Object | fine dining |
—
|
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: fine dining | Statement: [Ristorante Caterina de’ Medici, diningStyle, fine dining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: diningStyle Context triple: [Ristorante Caterina de’ Medici, diningStyle, fine dining]
-
A.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
B.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
-
C.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
D.
servesVenue
Indicates that an entity provides services or functions in support of a particular venue.
-
E.
servesAtThePleasureOf
Indicates that one entity holds a position or role that can be terminated at any time by another entity, typically at the discretion or will of that other entity.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25dae4a0c8190a66cf6ed3889851c |
completed | Feb. 28, 2026, 3:14 a.m. |
| PD | Predicate disambiguation | batch_69a25b70d99c819085d8381a313a2a34 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25d6ec9688190b2ba027756b57d25 |
completed | Feb. 28, 2026, 3:13 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.