Triple
T34165023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangus |
E876385
|
entity |
| Predicate | isPopularInCuisineOf |
P138036
|
FINISHED |
| Object | Philippines |
—
|
NE NERFINISHED |
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: Philippines | Statement: [Bangus, isPopularInCuisineOf, Philippines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPopularInCuisineOf Context triple: [Bangus, isPopularInCuisineOf, Philippines]
-
A.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
B.
isNationalDishOf
Indicates that a particular food is officially or culturally recognized as the national dish of a specific country or region.
-
C.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
D.
isOftenEaten
chosen
Indicates that the subject is frequently consumed as food by some agent or group.
-
E.
haveCuisine
Indicates that an entity (such as a restaurant or place) offers, serves, or is associated with a particular type or style of cuisine.
- 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_69f349ac987481908a8e6053f665bc8b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70fdedf708190ab68c2d567e086d0 |
completed | May 3, 2026, 9:05 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:54 a.m.