Triple
T27118100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyon, Rhône, France |
E686908
|
entity |
| Predicate | gastronomySpecialty |
P6863
|
FINISHED |
| Object | bouchon 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: bouchon restaurants | Statement: [Lyon, Rhône, France, gastronomySpecialty, bouchon restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gastronomySpecialty Context triple: [Lyon, Rhône, France, gastronomySpecialty, bouchon restaurants]
-
A.
foodCulture
Indicates the relationship between a place or group and its characteristic traditions, practices, and preferences surrounding food and eating.
-
B.
cuisine
chosen
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
C.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
E.
traditionalFoodBase
Indicates that one entity serves as the primary ingredient, staple, or foundational component of a traditional food associated with another entity.
- 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_69ef148c2b588190afc15b529f7af845 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6244119d0819081b22d365f9b907d |
completed | May 2, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69f61b40f02081909bd9c3ea73249163 |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 8:57 a.m.