Triple

T13102715
Position Surface form Disambiguated ID Type / Status
Subject Gung Ho E310758 entity
Predicate editor P1954 FINISHED
Object Daniel P. Hanley 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: Daniel P. Hanley | Statement: [Gung Ho, editor, Daniel P. Hanley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel P. Hanley
Context triple: [Gung Ho, editor, Daniel P. Hanley]
  • A. Daniel P. Hanley chosen
    Daniel P. Hanley is an American film editor best known for his long-time collaboration with director Ron Howard on numerous major Hollywood films.
  • B. Daniel P. Higgins
    Daniel P. Higgins was an architect associated with the design work on the Jefferson Memorial in Washington, D.C.
  • C. David P. Haney
    David P. Haney is an American academic administrator who has served as president of Hiram College in Ohio.
  • D. Allen M. Davey
    Allen M. Davey was an American cinematographer known for his work on early Technicolor films in Hollywood.
  • E. Leland J. Hamlin
    Leland J. Hamlin is an individual notable enough to be specifically cited as a bearer of the Hamlin surname, though detailed public information about his life or achievements appears to be limited.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98153255c8190b6ab64ac0c4716f8 completed April 10, 2026, 11:01 p.m.
Created at: April 9, 2026, 9:04 p.m.