Triple
T34390797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diamante |
E882695
|
entity |
| Predicate | hasGastronomySpecialty |
P17971
|
FINISHED |
| Object | chili pepper-based 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: chili pepper-based dishes | Statement: [Diamante, hasGastronomySpecialty, chili pepper-based dishes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGastronomySpecialty Context triple: [Diamante, hasGastronomySpecialty, chili pepper-based dishes]
-
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.
hasCulinaryTrend
Indicates a relationship where one entity exhibits, follows, or is characterized by a particular culinary trend associated with another entity.
-
E.
hasCuisineItem
Indicates that a particular cuisine includes, features, or is associated with a specific food item.
- 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_69f349c0219881909393bbbc1edc8161 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:59 a.m.