Triple

T10367380
Position Surface form Disambiguated ID Type / Status
Subject Strike Back E244289 entity
Predicate stars P1956 FINISHED
Object Warren Brown E252122 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: Warren Brown | Statement: [Strike Back, stars, Warren Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Warren Brown
Context triple: [Strike Back, stars, Warren Brown]
  • A. Warren Brown chosen
    Warren Brown is a British actor best known for his role as DS Justin Ripley in the crime drama series "Luther."
  • B. Warren Clarke
    Warren Clarke was a British character actor known for his powerful performances in film and television, including notable roles in "A Clockwork Orange" and the series "Dalziel and Pascoe."
  • C. Reynold Brown
    Reynold Brown was an American illustrator best known for his dramatic and dynamic movie poster art for numerous mid-20th-century Hollywood films, especially in the science fiction and horror genres.
  • D. Ray Merrimen
    Ray Merrimen is a disciplined, battle-hardened ex-Marine and mastermind leader of a crew of professional bank robbers in the crime film "Den of Thieves."
  • E. Hal Barwood
    Hal Barwood is an American filmmaker, screenwriter, and video game designer best known for his work on films like "Close Encounters of the Third Kind" and for creating story-driven adventure games at LucasArts.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e96fd6f081908f630a16106996d9 completed April 7, 2026, 11:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fb8e96e081908282bb0f82719abe completed April 9, 2026, 7:18 p.m.
Created at: April 6, 2026, noon