Triple
T21524349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Next Stop Wonderland |
E531055
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jose Zuniga |
—
|
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: Jose Zuniga | Statement: [Next Stop Wonderland, starring, Jose Zuniga]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jose Zuniga Context triple: [Next Stop Wonderland, starring, Jose Zuniga]
-
A.
Roberto Muzquiz
Roberto Muzquiz is the child of Rosaura De la Garza, a member of her immediate family.
-
B.
José Zúñiga
chosen
José Zúñiga is a Honduran-American character actor known for his numerous supporting roles in film and television, often portraying law enforcement or military figures.
-
C.
Reynaldo Villalobos
Reynaldo Villalobos is a cinematographer best known for his work on notable American films such as the comedy classic "9 to 5."
-
D.
Jorge Gutiérrez
Jorge Gutiérrez is a Mexican professional basketball player and former standout guard for the University of California, Berkeley, who went on to play in the NBA and internationally.
-
E.
Guillermo Magaña
Guillermo Magaña is a person notable enough to be recognized as a bearer of the surname Magaña, though specific widely known public details about him are not clearly established.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee884f4504819086bd632e62f02f58 |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:26 p.m.