Triple
T16790130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vinaròs |
E408082
|
entity |
| Predicate | hasSeafoodSpecialty |
P17971
|
FINISHED |
| Object | Vinaròs prawns |
—
|
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: Vinaròs prawns | Statement: [Vinaròs, hasSeafoodSpecialty, Vinaròs prawns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeafoodSpecialty Context triple: [Vinaròs, hasSeafoodSpecialty, Vinaròs prawns]
-
A.
seafoodSpecialty
Indicates that one entity specializes in preparing, serving, or producing seafood as a primary focus or notable expertise.
-
B.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty food.
-
C.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
-
D.
hasUnderwaterThemedRestaurant
Indicates that an entity operates or contains a restaurant whose design, ambiance, or concept is themed around underwater or oceanic elements.
-
E.
hasSeasideRestaurants
Indicates that a place or area contains restaurants located by or directly facing the sea.
- 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_69d8839270588190886720d9519bbf8f |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3b2a50e18819090a30e1f38e520e0 |
completed | April 18, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69e319cf691c819083e39225f5777ef0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:22 a.m.