Triple
T7602513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vélez |
E180017
|
entity |
| Predicate | hasLocalCuisineSpecialty |
P17971
|
FINISHED |
| Object | dulces típicos |
—
|
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: dulces típicos | Statement: [Vélez, hasLocalCuisineSpecialty, dulces típicos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalCuisineSpecialty Context triple: [Vélez, hasLocalCuisineSpecialty, dulces típicos]
-
A.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
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.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
D.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
-
E.
isNationalDishOf
Indicates that a particular food is officially or culturally recognized as the national dish of a specific country or region.
- 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_69c69f3567008190ab01d2ca7b53584a |
completed | March 27, 2026, 3:16 p.m. |
| NER | Named-entity recognition | batch_69c6f9f8e7848190b44d9c16b9c95d37 |
completed | March 27, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e485f88190910b39da52a955fe |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:54 p.m.