Triple
T12031734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virginie Ledoyen |
E286429
|
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: [Virginie Ledoyen, familyName, Fernández]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fernández Context triple: [Virginie Ledoyen, familyName, Fernández]
-
A.
Fernández
chosen
Fernández is a common Spanish-language surname widely used across Spain and Latin America.
-
B.
Fernández Vial
Fernández Vial is a Chilean football club based in Concepción, known for its historic roots and passionate local support.
-
C.
Pérez
Pérez is a common Spanish-language surname widely found in Spain and Latin America.
-
D.
Garzón
Garzón is a municipality and town in south-central Colombia known as an agricultural center within the Huila Department.
-
E.
Ellacuría
Ellacuría is a Basque-origin surname most notably associated with Ignacio Ellacuría, a Spanish-Salvadoran Jesuit priest, philosopher, and prominent liberation theologian.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903f24490819092ec911d6ed8e24b |
completed | April 10, 2026, 2:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f49d5fd0708190860201a4a8c6fe7c |
completed | May 1, 2026, 12:32 p.m. |
Created at: April 8, 2026, 9:47 p.m.