Triple
T31699562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atripalda |
E809013
|
entity |
| Predicate | localCuisineRegion |
P45120
|
FINISHED |
| Object | Irpinian cuisine |
—
|
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: Irpinian cuisine | Statement: [Atripalda, localCuisineRegion, Irpinian cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localCuisineRegion Context triple: [Atripalda, localCuisineRegion, Irpinian cuisine]
-
A.
includesRegionalCuisine
Indicates that one entity incorporates or features the regional cuisine associated with another entity.
-
B.
ethnicRegionalBase
Indicates that an entity’s support, identity, or operations are primarily rooted in a specific ethnic group within a particular geographic region.
-
C.
regionOfCulinaryImportance
chosen
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
D.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
E.
homeCountryRegion
Indicates the country or broader geographic region that is considered the primary home or origin of an 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_69f348de914081909fc8edff56f34dbe |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: April 30, 2026, 11:11 p.m.