Triple
T34094708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Premio Nacional de Danza |
E874392
|
entity |
| Predicate | áreaGeográfica |
P178224
|
FINISHED |
| Object | territorio español |
—
|
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: territorio español | Statement: [Premio Nacional de Danza, áreaGeográfica, territorio español]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: áreaGeográfica Context triple: [Premio Nacional de Danza, áreaGeográfica, territorio español]
-
A.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
B.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
C.
ianaArea
Indicates that one entity is associated with, or falls within, a specific IANA-defined geographic or administrative area represented by the other entity.
-
D.
metroArea
Indicates that one location is part of, or belongs to, a specified metropolitan area.
-
E.
geographicDivision
Indicates that one place is an administrative or territorial subdivision of another place.
- F. None of above. chosen
Provenance (4 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f70c5991108190a09fc0faf6cb49d2 |
completed | May 3, 2026, 8:50 a.m. |
| PD | Predicate disambiguation | batch_69f70ac0170c819098e3b8e41d02efef |
completed | May 3, 2026, 8:43 a.m. |
| PDg | Predicate description generation | batch_69f70b94784c8190970d654e066eb50d |
completed | May 3, 2026, 8:47 a.m. |
Created at: May 1, 2026, 1:52 a.m.