Triple

T597444
Position Surface form Disambiguated ID Type / Status
Subject Nicholas Nickleby (2002 film) E11417 entity
Predicate screenwriter P2831 FINISHED
Object Douglas McGrath E141781 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: Douglas McGrath | Statement: [Nicholas Nickleby (2002 film), screenwriter, Douglas McGrath]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Douglas McGrath
Context triple: [Nicholas Nickleby (2002 film), screenwriter, Douglas McGrath]
  • A. Douglas McGrath chosen
    Douglas McGrath was an American screenwriter, director, and actor known for his literary adaptations and collaborations with Woody Allen.
  • B. Rob McKenna
    Rob McKenna is an American attorney and politician best known for serving as the Attorney General of Washington State.
  • C. Rob McKenna
    Rob McKenna is a perpetually rain-plagued lorry driver in Douglas Adams' "So Long, and Thanks for All the Fish," humorously revealed to be a Rain God unknowingly worshipped by clouds.
  • D. Laird Doyle
    Laird Doyle was an American screenwriter active in early Hollywood, known for adapting literary works for the screen.
  • E. Andrew Duggan
    Andrew Duggan was an American character actor known for his prolific work in film and television from the 1950s through the 1980s.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d2b98d08190a1c1e8659efdfd75 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93942b1c819087f6fdef027f115e completed March 7, 2026, 9:07 p.m.
Created at: March 1, 2026, 7:35 p.m.