Triple
T18173229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ben-Hur (2016 film) |
E435084
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Sean Daniel |
—
|
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: Sean Daniel | Statement: [Ben-Hur (2016 film), producer, Sean Daniel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sean Daniel Context triple: [Ben-Hur (2016 film), producer, Sean Daniel]
-
A.
Sean Daniel
chosen
Sean Daniel is an American film producer known for working on major Hollywood genre films, including horror and fantasy franchises.
-
B.
Ben Daniels
Ben Daniels is an English actor known for his work in film, television, and theatre, including roles in projects such as the 2005 film adaptation of "Doom" and the series "The Exorcist" and "House of Cards."
-
C.
Sean Sagar
Sean Sagar is a British actor known for roles in television dramas and action series, including a part in the NCIS franchise spin-off NCIS: Sydney.
-
D.
Matt Weinberg
Matt Weinberg is an American former child actor best known for his voice and on-screen roles in film and television during the late 1990s and early 2000s.
-
E.
Jonathan Sanger
Jonathan Sanger is an American film producer and director best known for his work on acclaimed films such as "The Elephant Man."
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df583a8081908c07d3534091c2ae |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 10:30 a.m.