Triple

T8329261
Position Surface form Disambiguated ID Type / Status
Subject Tár E195033 entity
Predicate producer P490 FINISHED
Object Todd Field E364798 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: Todd Field | Statement: [Tár, producer, Todd Field]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Todd Field
Context triple: [Tár, producer, Todd Field]
  • A. Todd Field chosen
    Todd Field is an American filmmaker, screenwriter, and former actor best known for directing critically acclaimed films such as "In the Bedroom," "Little Children," and "Tár."
  • B. Oren Moverman
    Oren Moverman is an Israeli-American screenwriter and director known for his work on acclaimed films such as "I'm Not There," "The Messenger," and "Rampart."
  • C. Bill Condon
    Bill Condon is an American film director and screenwriter known for works such as "Gods and Monsters," "Dreamgirls," and Disney's live-action "Beauty and the Beast."
  • D. Todd Haynes
    Todd Haynes is an American film director and screenwriter known for his innovative, genre-challenging works such as "Far from Heaven," "Carol," and "Safe," often exploring themes of identity, sexuality, and social norms.
  • E. Tate Taylor
    Tate Taylor is an American filmmaker and actor best known for directing films such as "The Help," "Get on Up," and the thriller "The Girl on the Train."
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fb812508190aed8a283dacf712e completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce028586788190b07c601e521eb531 completed April 2, 2026, 5:45 a.m.
Created at: March 30, 2026, 5:56 p.m.