Triple

T6791167
Position Surface form Disambiguated ID Type / Status
Subject About a Boy E155934 entity
Predicate screenwriter P2831 FINISHED
Object Peter Hedges E276002 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: Peter Hedges | Statement: [About a Boy, screenwriter, Peter Hedges]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Hedges
Context triple: [About a Boy, screenwriter, Peter Hedges]
  • A. Peter Hedges chosen
    Peter Hedges is an American novelist, playwright, and filmmaker best known for writing the novel and screenplay for "What's Eating Gilbert Grape" and directing films such as "Pieces of April" and "Dan in Real Life."
  • B. Sacha Gervasi
    Sacha Gervasi is a British screenwriter and director known for films such as "The Terminal" and the documentary "Anvil! The Story of Anvil."
  • C. Dan Gilroy
    Dan Gilroy is an American screenwriter and director best known for writing and directing the critically acclaimed film "Nightcrawler."
  • D. Dan Goor
    Dan Goor is an American television writer and producer best known for co-creating the comedy series "Brooklyn Nine-Nine" and his work on shows like "Parks and Recreation."
  • E. Michael Arndt
    Michael Arndt is an Academy Award–winning American screenwriter known for acclaimed films such as Little Miss Sunshine and Toy Story 3.
  • 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_69c6881770fc8190972b2906390380f5 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2acbfc0819081f2d6cebfb91765 completed March 27, 2026, 6:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69c72f94b7388190806939f8e8982d2e completed March 28, 2026, 1:32 a.m.
Created at: March 27, 2026, 2:15 p.m.