Triple

T3226931
Position Surface form Disambiguated ID Type / Status
Subject Abbott Lawrence E67645 entity
Predicate marriedTo P13 FINISHED
Object Katherine 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: Katherine Bigelow | Statement: [Abbott Lawrence, marriedTo, Katherine Bigelow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katherine Bigelow
Context triple: [Abbott Lawrence, marriedTo, Katherine 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. Jocelyn Moorhouse
    Jocelyn Moorhouse is an Australian film director and screenwriter known for character-driven dramas such as "Proof" and "How to Make an American Quilt."
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb5e67c819082070d108d3613ba completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69b26262af848190a918f3a606bfa616 completed March 12, 2026, 6:51 a.m.
Created at: March 8, 2026, 3:08 p.m.