Triple

T4626306
Position Surface form Disambiguated ID Type / Status
Subject The Other Man E101105 entity
Predicate screenwriter P2831 FINISHED
Object Charles Wood E463219 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: Charles Wood | Statement: [The Other Man, screenwriter, Charles Wood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Wood
Context triple: [The Other Man, screenwriter, Charles Wood]
  • A. Charles Wood chosen
    Charles Wood was a British playwright and screenwriter known for his sharp, satirical writing and influential work in film, television, and theatre.
  • B. John Palmer
    John Palmer is a film industry professional known for his work as an assistant director, including on the movie "Empire."
  • C. Hugh McDowell
    Hugh McDowell was an English cellist best known for his dynamic performances and recordings with the rock band Electric Light Orchestra during the 1970s.
  • D. Charles Heath
    Charles Heath was a prominent 19th-century English engraver known for his book illustrations and contributions to the popularization of steel engraving.
  • E. Robert Woodlark
    Robert Woodlark was a 15th-century English priest and academic who served as Provost of King’s College, Cambridge, and is best known for establishing St Catharine’s College at the University of Cambridge.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a0a7b588190bc6552ee5babb198 completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69be399de7248190ba4cde67ff4cbff4 completed March 21, 2026, 6:24 a.m.
Created at: March 20, 2026, 1:13 p.m.