Triple
T4498822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oyón Province |
E100765
|
entity |
| Predicate | hasMunicipalSeat |
P1474
|
FINISHED |
| Object | Oyón |
E448072
|
NE 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: Oyón | Statement: [Oyón Province, hasMunicipalSeat, Oyón]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oyón Context triple: [Oyón Province, hasMunicipalSeat, Oyón]
-
A.
Oyón
chosen
Oyón is a town in Peru that serves as the administrative and commercial center of the surrounding Oyón Province in the highlands.
-
B.
Requena
Requena is a historic inland town in Spain’s Valencian Community, known for its wine production and well-preserved medieval quarter.
-
C.
Hinojosa
Hinojosa is a Spanish surname historically associated with figures such as José de la Serna e Hinojosa, the last viceroy of Peru.
-
D.
Rivas
Rivas is a city in southwestern Nicaragua known as a regional commercial center and gateway between Lake Nicaragua and the Pacific coast.
-
E.
Aguadas
Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd43cdf15081909a4fa2585ff63b3e |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56c29868819097633c7cd398e865 |
completed | March 20, 2026, 2:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bda41dd58081908b8d8779a71f3c97 |
completed | March 20, 2026, 7:46 p.m. |
Created at: March 20, 2026, 1 p.m.