Triple
T19504919
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Russian Doll |
E487997
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Yul Vazquez |
—
|
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: Yul Vazquez | Statement: [Russian Doll, castMember, Yul Vazquez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yul Vazquez Context triple: [Russian Doll, castMember, Yul Vazquez]
-
A.
Yul Vazquez
chosen
Yul Vazquez is a Cuban-American actor known for his character roles in film and television, including appearances in projects like "Severance," "Captain Phillips," and "The Outsider."
-
B.
Gabriel Luna
Gabriel Luna is an American actor best known for roles in projects like Marvel’s Agents of S.H.I.E.L.D., Terminator: Dark Fate, and the HBO adaptation of The Last of Us.
-
C.
Tony Aviña
Tony Aviña is a comic book colorist known for his work on titles such as the espionage series "Sleeper."
-
D.
Daniel Zaragoza
Daniel Zaragoza is a former Mexican professional boxer and long-reigning WBC super bantamweight champion known for his awkward southpaw style and multiple world title reigns.
-
E.
Jacob Vargas
Jacob Vargas is a Mexican-American actor known for his versatile roles in film and television, including notable performances in projects like "Traffic," "Selena," and "Jarhead."
- 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635113fdc819098ea0f738d01925c |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.