Triple

T20575694
Position Surface form Disambiguated ID Type / Status
Subject Red Dust E505211 entity
Predicate screenplayBy P15305 FINISHED
Object Troy Kennedy Martin 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: Troy Kennedy Martin | Statement: [Red Dust, screenplayBy, Troy Kennedy Martin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troy Kennedy Martin
Context triple: [Red Dust, screenplayBy, Troy Kennedy Martin]
  • A. Troy Kennedy Martin chosen
    Troy Kennedy Martin was a British television and film screenwriter best known for creating the series "Z-Cars" and writing the original 1969 film "The Italian Job."
  • B. Aaron McKinney
    Aaron McKinney is an American man best known as one of the two assailants convicted in the 1998 murder of Matthew Shepard, a crime that drew national attention to anti-LGBTQ+ hate violence.
  • C. Henry Bowers
    Henry Bowers is a sadistic teenage bully and one of the primary human antagonists in the 2017 horror film adaptation of Stephen King’s "It."
  • D. Mel Stride
    Mel Stride is a British Conservative Party politician who has served as a Member of Parliament and held various ministerial roles in the UK government.
  • E. John Crawford
    John Crawford was an American character actor known for his numerous supporting roles in film and television from the 1940s through the 1980s.
  • 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_69e0b4b721588190993ac7b0a9be2736 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a909785c8190a02b1195eadb384c completed April 20, 2026, 10:30 p.m.
Created at: April 16, 2026, 11:39 a.m.