Triple
T18283051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heaven Sent |
E437910
|
entity |
| Predicate | producedBy |
P490
|
FINISHED |
| Object | Peter 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: Peter Bennett | Statement: [Heaven Sent, producedBy, Peter Bennett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Bennett Context triple: [Heaven Sent, producedBy, Peter Bennett]
-
A.
Peter Bennett
chosen
Peter Bennett is a British television producer best known for his work on the long-running sci-fi series Doctor Who and its related projects.
-
B.
Keith Bennett
Keith Bennett was a 12-year-old English boy who became one of the child victims of the notorious Moors murders committed by Ian Brady and Myra Hindley in the 1960s.
-
C.
Peter Bennett-Jones
Peter Bennett-Jones is a British television and film producer and talent agent best known for his work on hit comedies such as "Mr. Bean" and for founding the production company Tiger Aspect.
-
D.
Don Bennett
Don Bennett was an Australian-born Royal Air Force officer best known for leading and pioneering advanced navigation techniques in the RAF’s elite Pathfinder Force during World War II.
-
E.
Stephen Buckley
Stephen Buckley is a name shared by several notable individuals, including professionals in fields such as academia, sports, and the arts.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50057c5c881909fcda72f4a98c8c3 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 10:35 a.m.