Triple
T2298878
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Víctor Manuel Fernández |
E51682
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fernández |
E42933
|
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: Fernández | Statement: [Víctor Manuel Fernández, familyName, Fernández]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fernández Context triple: [Víctor Manuel Fernández, familyName, Fernández]
-
A.
Fernández
chosen
Fernández is a common Spanish-language surname widely used across Spain and Latin America.
-
B.
Garzón
Garzón is a municipality and town in south-central Colombia known as an agricultural center within the Huila Department.
-
C.
Mariano
Mariano is a masculine given name of Spanish and Portuguese origin, commonly used in various Spanish-speaking and Latin cultures.
-
D.
Sánchez
Sánchez is a common Spanish-language surname borne by numerous notable figures across sports, politics, arts, and other fields.
-
E.
Hernández
Hernández is a common Spanish surname borne by numerous notable figures across sports, arts, and public life.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5ec3c948190b47ea763812a1cf5 |
completed | March 7, 2026, 6:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae7f2e338881908e09d19f469a59ce |
completed | March 9, 2026, 8:05 a.m. |
Created at: March 4, 2026, 7:49 p.m.