Triple

T3593833
Position Surface form Disambiguated ID Type / Status
Subject Mark Boal E76088 entity
Predicate collaboratedWith P435 FINISHED
Object Kathryn Bigelow E54556 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: Kathryn Bigelow | Statement: [Mark Boal, collaboratedWith, Kathryn Bigelow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kathryn Bigelow
Context triple: [Mark Boal, collaboratedWith, Kathryn Bigelow]
  • A. Kathryn Bigelow chosen
    Kathryn Bigelow is an American film director and producer best known for her gritty, suspenseful dramas such as "The Hurt Locker" and "Zero Dark Thirty."
  • B. Kasi Lemmons
    Kasi Lemmons is an American film director, screenwriter, and actress known for works such as "Eve's Bayou," "Harriet," and other character-driven dramas exploring African American experiences.
  • C. Cate Shortland
    Cate Shortland is an Australian film and television director known for character-driven dramas and for directing the Marvel superhero film "Black Widow."
  • D. Sandy Powell
    Sandy Powell is a renowned British costume designer celebrated for her innovative and influential work on numerous acclaimed films.
  • E. Gale Anne Hurd
    Gale Anne Hurd is an American film and television producer best known for her influential work on science fiction and action franchises such as The Terminator and Aliens.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15d3e308190b8352ef1f054f9c3 completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4030fab188190b8de1a4b4d625f00 completed March 13, 2026, 12:29 p.m.
Created at: March 8, 2026, 3:22 p.m.