Triple
T20355545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicente Fernández |
E496635
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object | Alejandro Fernández |
—
|
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: Alejandro Fernández | Statement: [Vicente Fernández, child, Alejandro Fernández]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alejandro Fernández Context triple: [Vicente Fernández, child, Alejandro Fernández]
-
A.
Alejandro Fernández
chosen
Alejandro Fernández is a renowned Mexican singer celebrated for his powerful vocals and successful career spanning traditional ranchera and Latin pop music.
-
B.
Alejandro Sanz
Alejandro Sanz is a Spanish singer-songwriter and musician renowned for his romantic ballads and multiple Grammy and Latin Grammy Awards.
-
C.
Cristian Castro
Cristian Castro is a Mexican pop singer known for his powerful vocals and numerous Latin American hits since the early 1990s.
-
D.
Luis Miguel
Luis Miguel is a Mexican singer widely regarded as one of the most successful and influential Latin music artists of all time.
-
E.
Carlos Sanz
Carlos Sanz is a Spanish-American character actor known for his supporting roles in action and crime films and television series.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67853f10881908ecde94036804a8a |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.