Triple
T19844426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juan Bautista Topete |
E476819
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Bautista |
—
|
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: Bautista | Statement: [Juan Bautista Topete, hasGivenName, Bautista]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bautista Context triple: [Juan Bautista Topete, hasGivenName, Bautista]
-
A.
Bautista
chosen
Bautista is a Spanish-origin surname common in the Hispanic world and borne by numerous notable figures in sports, politics, and the arts.
-
B.
Ceballos
Ceballos is a Spanish surname borne by various notable figures in politics, sports, and the arts.
-
C.
Barbarito Torres
Barbarito Torres is a Cuban laud player and musician best known for his work with the Buena Vista Social Club collective that helped revive global interest in traditional Cuban music.
-
D.
Carrasco
Carrasco is a Spanish-language surname borne by various notable individuals across sports, politics, and the arts.
-
E.
Berto
Berto is a diminutive or short given name commonly used as an affectionate or informal form of longer names such as Humbert.
- 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_69d8e51d39d081909bcfafeaaf3d2fcc |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658085a148190a305bde0897dfe84 |
completed | April 20, 2026, 4:44 p.m. |
Created at: April 10, 2026, 1:51 p.m.