Triple
T17463299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fidel Dávila Arrondo |
E425211
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Dávila |
—
|
NE NERFINISHED |
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: Dávila | Statement: [Fidel Dávila Arrondo, familyName, Dávila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dávila Context triple: [Fidel Dávila Arrondo, familyName, Dávila]
-
A.
Davila
chosen
Davila is an Italian surname most notably associated with the 17th-century historian Enrico Caterino Davila.
-
B.
Valladares
Valladares is a Spanish surname historically associated with nobility and notable figures such as colonial administrators and politicians.
-
C.
Montúfar
Montúfar is a Spanish-origin surname historically associated with notable figures in Latin American colonial and independence-era history.
-
D.
Giménez
Giménez is a Spanish-language surname commonly found in Spain and Latin American countries, borne by various notable figures in sports, arts, and public life.
-
E.
Diéguez
Diéguez is a Spanish-language surname of Galician origin borne by various notable individuals, including figures in the arts and public life.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dbc2e88190b18ea6115e819258 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451a4c36c81909c7c4b1b0d976921 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:47 a.m.