Triple
T2484891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nariño |
E55901
|
entity |
| Predicate | hasTraditionalCuisine |
P19483
|
FINISHED |
| Object | cuy (guinea pig) |
—
|
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: cuy (guinea pig) | Statement: [Nariño, hasTraditionalCuisine, cuy (guinea pig)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalCuisine Context triple: [Nariño, hasTraditionalCuisine, cuy (guinea pig)]
-
A.
traditionalCuisine
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
B.
traditionalDish
chosen
Indicates that the object is a dish customarily prepared, eaten, or recognized within the subject’s cultural or regional tradition.
-
C.
hasTraditionIn
Indicates that a particular tradition, custom, or longstanding practice is present, observed, or established within a specified place, group, or context.
-
D.
cuisineFeature
Indicates a characteristic, quality, or notable aspect that describes or distinguishes a particular cuisine.
-
E.
hasSpecialtyFood
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_69ab49e670a88190b928e08302381710 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd20b6d008190acec0eb172e218c9 |
completed | March 7, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69abd0b7cf088190bcff4dac6150044c |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:45 p.m.