Triple
T10956511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Never Die Young |
E258858
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Carlos Vega |
E944027
|
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: Carlos Vega | Statement: [Never Die Young, performer, Carlos Vega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carlos Vega Context triple: [Never Die Young, performer, Carlos Vega]
-
A.
Carlos Vega
chosen
Carlos Vega was a highly respected American session drummer known for his versatile work across pop, rock, and jazz recordings.
-
B.
Carlos Reyes
Carlos Reyes is a fictional Austin police officer and key ensemble character in the television drama series "9-1-1: Lone Star."
-
C.
Víctor Vázquez
Víctor Vázquez is a Spanish attacking midfielder known for his playmaking ability and key contributions to Toronto FC, including scoring in the 2017 MLS Cup final.
-
D.
Alonso Vega
Alonso Vega was an individual notable enough to be interred at Mingorrubio Cemetery in Madrid, Spain.
-
E.
Carlos Bustamante
Carlos Bustamante is a prominent Peruvian-American population geneticist and Stanford professor known for his influential work on human genetic diversity and its applications to medicine and ancestry.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771260e9881909401a7a7466e1b8a |
completed | April 9, 2026, 9:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f416ab88e48190b3089caab7987191 |
completed | May 1, 2026, 2:57 a.m. |
Created at: April 8, 2026, 9:23 p.m.