Triple
T12557699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alejandro Castro Espín |
E295260
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Espín |
E293418
|
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: Espín | Statement: [Alejandro Castro Espín, familyName, Espín]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Espín Context triple: [Alejandro Castro Espín, familyName, Espín]
-
A.
Espín
chosen
Espín is a Spanish surname notably borne by Cuban revolutionary and feminist leader Vilma Espín.
-
B.
Espinar
Espinar is a town in southern Peru that serves as an administrative and commercial center in the Andean highlands.
-
C.
Osuna
Osuna is a historic town in the province of Seville, Spain, known for its rich archaeological heritage, including notable ancient reliefs and other Roman-era remains.
-
D.
Mondragón
Mondragón is a historic town in Spain’s Basque Country, known for its medieval heritage and later as a center of cooperative industry.
-
E.
Olañeta
Olañeta is a Spanish Basque surname most notably associated with Pedro Antonio Olañeta, a royalist military leader during the Spanish American wars of independence.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d95491d9688190a6b88a939124233e |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655895c9c819082f41e79906567c6 |
completed | May 2, 2026, 7:50 p.m. |
Created at: April 8, 2026, 11:47 p.m.