Triple

T3239791
Position Surface form Disambiguated ID Type / Status
Subject Raw (stand-up film) E67939 entity
Predicate director P255 FINISHED
Object Robert Townsend E268044 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: Robert Townsend | Statement: [Raw (stand-up film), director, Robert Townsend]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Robert Townsend
Context triple: [Raw (stand-up film), director, Robert Townsend]
  • A. Robert Townsend chosen
    Robert Townsend is an American actor, director, and filmmaker known for his influential work in African-American cinema, including films like "Hollywood Shuffle" and "The Five Heartbeats."
  • B. Norman Lloyd
    Norman Lloyd was an American actor, producer, and director whose career in film, television, and theater spanned more than eight decades.
  • C. Robert Allen
    Robert Allen was an American film actor active in the 1930s, best known for his roles in Westerns and crime dramas.
  • D. Robert McLane
    Robert McLane was an American businessman best known as the founder of McLane Company, a major supply chain services and wholesale distribution firm.
  • E. Don Hahn
    Don Hahn is an American film producer best known for overseeing several of Disney’s most acclaimed animated features, including Beauty and the Beast and The Lion King.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef4c0bc819095e4f84296fe7cb6 completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a65d2988190a053eb2f22503f83 completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:08 p.m.