Triple
T10537166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santos Degollado |
E248598
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Degollado |
E659923
|
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: Degollado | Statement: [Santos Degollado, familyName, Degollado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Degollado Context triple: [Santos Degollado, familyName, Degollado]
-
A.
Degollado
chosen
Degollado is a small city in the Ciénega region of Jalisco, Mexico, known for its agricultural economy and traditional rural character.
-
B.
Diéguez
Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
-
C.
Balderas
Balderas is a major Mexico City Metro station known for its central location and high passenger traffic.
-
D.
Alvarado
Alvarado is a historic port city in the Mexican state of Veracruz, known for its fishing industry and location near the Gulf of Mexico.
-
E.
Navarrete
Navarrete is a Spanish surname most notably borne by Javier Navarrete, an acclaimed film composer known for his work on movies such as "Pan's Labyrinth."
- 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a554fb4819081e9618bab051dc6 |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90e5b827881909e87651a88976f18 |
completed | April 10, 2026, 2:51 p.m. |
Created at: April 6, 2026, 12:31 p.m.