Triple

T20462357
Position Surface form Disambiguated ID Type / Status
Subject Detective Story E501956 entity
Predicate cinematographer P1953 FINISHED
Object Lee Garmes NE NERFINISHED

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: Lee Garmes | Statement: [Detective Story, cinematographer, Lee Garmes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lee Garmes
Context triple: [Detective Story, cinematographer, Lee Garmes]
  • A. Lee Garmes chosen
    Lee Garmes was an American cinematographer renowned for his innovative lighting and camera techniques in early Hollywood cinema, including his Academy Award-winning work on "Shanghai Express."
  • B. Lee Klarich
    Lee Klarich is a technology executive best known as a key founding leader and longtime chief product officer of cybersecurity company Palo Alto Networks.
  • C. Ben Klibreck
    Ben Klibreck is a prominent mountain in the Scottish Highlands, known for its isolated position and sweeping views over the county of Sutherland.
  • D. Ed Herendeen
    Ed Herendeen is an American theater producer and artistic director best known as the founder and longtime leader of the Contemporary American Theater Festival, a prominent showcase for new plays.
  • E. Frank Doelger
    Frank Doelger is a television producer best known for his work on the acclaimed HBO fantasy series "Game of Thrones."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a761648190b24cf4bb90a8abb1 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.