Triple

T577827
Position Surface form Disambiguated ID Type / Status
Subject Splash E13794 entity
Predicate editedBy P1954 FINISHED
Object Daniel P. Hanley E114053 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: Daniel P. Hanley | Statement: [Splash, editedBy, Daniel P. Hanley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel P. Hanley
Context triple: [Splash, editedBy, 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. Patrick E. Haggerty
    Patrick E. Haggerty was an American engineer and business executive who played a pivotal role in the early semiconductor industry and the growth of Texas Instruments into a major technology company.
  • D. James A. Abrahamson
    James A. Abrahamson is a retired U.S. Air Force lieutenant general and aerospace engineer best known for directing NASA’s Space Shuttle program and leading the Strategic Defense Initiative Organization in the 1980s.
  • E. Alan M. Garber
    Alan M. Garber is an American physician-economist and academic leader known for his work in health policy and for serving in top administrative roles at Harvard University.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b69fed88190b5558d4ebd5047a1 completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf39f5694819086fcdbd27fa2ea4b completed March 8, 2026, 10:09 p.m.
Created at: March 1, 2026, 7:33 p.m.