Triple

T9854160
Position Surface form Disambiguated ID Type / Status
Subject While She Was Out E239542 entity
Predicate producer P490 FINISHED
Object Don Murphy E651597 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: Don Murphy | Statement: [While She Was Out, producer, Don Murphy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Murphy
Context triple: [While She Was Out, producer, Don Murphy]
  • A. Don Murphy chosen
    Don Murphy is an American film producer best known for helping launch and produce the live-action Transformers film franchise.
  • B. Dennis Murphy
    Dennis Murphy was an American sports entrepreneur best known for co-founding several upstart professional leagues, including the American Basketball Association.
  • C. Phil Burke
    Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
  • D. Don Carmody
    Don Carmody is a prolific Canadian film producer known for his work on numerous commercially successful and cult-favorite films across genres.
  • E. Michael Maloney
    Michael Maloney is a British actor known for his work in film, television, and theatre, including prominent roles in Shakespearean adaptations.
  • 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_69ca84e4fdc08190a624425bcef98665 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3960fb481909c90d6d6cafc6222 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2e519c7a88190b8776b4af4908d1f completed April 5, 2026, 10:41 p.m.
Created at: March 30, 2026, 8:34 p.m.