Triple
T7818890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sant’Angelo village |
E181078
|
entity |
| Predicate | localCuisineFeatures |
P17157
|
FINISHED |
| Object | seafood dishes |
—
|
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: seafood dishes | Statement: [Sant’Angelo village, localCuisineFeatures, seafood dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: localCuisineFeatures Context triple: [Sant’Angelo village, localCuisineFeatures, seafood dishes]
-
A.
cuisineFeature
chosen
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
B.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
C.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
D.
alsoEats
Indicates that an entity consumes something in addition to another item or items it already eats.
-
E.
foodCustom
Indicates a culturally specific practice, rule, or tradition related to the preparation, serving, or consumption of food.
- 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_69ca828153f48190bdb27ac46f8e0745 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf97247c481908b18287eb7ee0a53 |
completed | March 30, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:40 p.m.