Triple
T20390574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Narrow Margin |
E498072
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Nigel Bennett |
—
|
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: Nigel Bennett | Statement: [Narrow Margin, starring, Nigel Bennett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nigel Bennett Context triple: [Narrow Margin, starring, Nigel Bennett]
-
A.
Nigel Bennett
chosen
Nigel Bennett is a British-born Canadian actor and director best known for his character roles in film and television, including crime dramas and genre series.
-
B.
Nigel Thornberry
Nigel Thornberry is a bumbling yet enthusiastic British wildlife documentarian and father, known for his exaggerated mannerisms, distinctive voice, and comedic mishaps in the animated series The Wild Thornberrys.
-
C.
Neil Agnew
Neil Agnew was the first husband of American actress and television personality Arlene Francis.
-
D.
Norman Stansfield
Norman Stansfield is the sadistic, drug-addicted DEA agent and primary antagonist portrayed by Gary Oldman in the film "Léon: The Professional."
-
E.
Graham Baldwin
Graham Baldwin is a British academic and university leader who serves as the vice-chancellor of the University of Central Lancashire.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790f8d9c819093038f6bb6f47a92 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.