Triple
T12541512
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chiclayo |
E299848
|
entity |
| Predicate | regionalCuisineSpecialty |
P17971
|
FINISHED |
| Object | seco de cabrito |
—
|
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: seco de cabrito | Statement: [Chiclayo, regionalCuisineSpecialty, seco de cabrito]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalCuisineSpecialty Context triple: [Chiclayo, regionalCuisineSpecialty, seco de cabrito]
-
A.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
B.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
C.
cuisineSubtype
Indicates that one cuisine is a more specific subtype or variant within the broader category of another cuisine.
-
D.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
-
E.
hasSpecialtyFood
chosen
Indicates that an entity offers, serves, or is associated with a particular type of specialty 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_69d6ada707008190aaec1238117c9379 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95f5507b481908d13cc317b7402f6 |
completed | April 10, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_69d95410d0b0819097646edd1b837104 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.