Triple
T20080500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Física o química |
E499986
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Vaquero |
—
|
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: Vaquero | Statement: [Física o química, mainCharacter, Vaquero]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vaquero Context triple: [Física o química, mainCharacter, Vaquero]
-
A.
Vaquero
chosen
Vaquero is the cowboy-themed mascot representing the University of Texas Rio Grande Valley’s athletic teams.
-
B.
Pueblo Vaquero
Pueblo Vaquero is a Western-themed area within the Six Flags México amusement park, featuring attractions, decor, and entertainment inspired by traditional cowboy towns.
-
C.
Don Criqui
Don Criqui is an American sportscaster best known for his long-running play-by-play work on NFL broadcasts and other major sporting events.
-
D.
Pancho
Pancho is a common Spanish nickname typically used as a familiar or affectionate form of the given name Francisco.
-
E.
Baquero
Baquero is a Spanish surname most notably associated with actress Ivana Baquero, known for her role in the film "Pan's Labyrinth."
- 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66557c19c8190b511857490bbd423 |
completed | April 20, 2026, 5:41 p.m. |
Created at: April 11, 2026, 3:41 p.m.