Triple

T16576993
Position Surface form Disambiguated ID Type / Status
Subject Doctor Who series 5 E402737 entity
Predicate producer P490 FINISHED
Object Peter Bennett E1219531 NE FINISHED

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: [Doctor Who series 5, producer, Peter Bennett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Bennett
Context triple: [Doctor Who series 5, producer, 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 (3 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_69d88387363c8190a97a0c942130de97 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3595dd90881909933216bd12505e1 completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0091891c5081908f37598a17417c94 completed May 10, 2026, 2:09 p.m.
Created at: April 10, 2026, 5:16 a.m.