Triple
T827696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vox |
E17891
|
entity |
| Predicate | president |
P8
|
FINISHED |
| Object | Santiago Abascal |
E96431
|
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: Santiago Abascal | Statement: [Vox, president, Santiago Abascal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santiago Abascal Context triple: [Vox, president, Santiago Abascal]
-
A.
Santiago Abascal
chosen
Santiago Abascal is a Spanish politician best known as the leader and co-founder of the right-wing populist party Vox.
-
B.
Ramón Carnicer
Ramón Carnicer was a 19th-century Spanish composer best known for writing the music of the Chilean national anthem.
-
C.
Julián Ruiz Gabiña
Julián Ruiz Gabiña was the husband of prominent Spanish communist leader and orator Dolores Ibárruri, known as "La Pasionaria."
-
D.
Eugenio Montero Ríos
Eugenio Montero Ríos was a Spanish jurist and politician who served as Prime Minister of Spain and played a key role in negotiating the end of the Spanish–American War.
-
E.
José Luzán
José Luzán was an 18th-century Spanish painter and influential teacher best known for mentoring the young Francisco Goya.
- 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab99b1e48190afad1f073348b29a |
completed | March 1, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3b6f0a0819086f8789773f8251e |
completed | March 4, 2026, 3:15 a.m. |
Created at: March 1, 2026, 7:38 p.m.