Triple

T11036969
Position Surface form Disambiguated ID Type / Status
Subject Doctor Who: The Movie E260910 entity
Predicate executiveProducer P7225 FINISHED
Object Philip Segal E742750 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: Philip Segal | Statement: [Doctor Who: The Movie, executiveProducer, Philip Segal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philip Segal
Context triple: [Doctor Who: The Movie, executiveProducer, Philip Segal]
  • A. Philip Segal chosen
    Philip Segal is a television producer best known for his work on genre and reality-based series, including serving as an executive producer on the darkly comedic show "1000 Ways to Die."
  • B. Douglas Segal
    Douglas Segal is a film producer best known for his work on the action-comedy movie "Bulletproof Monk."
  • C. J. David Siegel
    J. David Siegel is a film editor known for his work on major animated features, including the superhero comedy "DC League of Super-Pets."
  • D. Andrew Shulkind
    Andrew Shulkind is a cinematographer known for his atmospheric and visually immersive work in genre films and television.
  • E. Steven Fierberg
    Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
  • 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797e9e3fc8190802195ac9fcb8e28 completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e712e6288481908071e248a50209e0 completed April 21, 2026, 6:02 a.m.
Created at: April 8, 2026, 9:25 p.m.