Triple

T7354770
Position Surface form Disambiguated ID Type / Status
Subject Seems Like Old Times E169594 entity
Predicate cinematographyBy P1953 FINISHED
Object David M. Walsh E308850 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: David M. Walsh | Statement: [Seems Like Old Times, cinematographyBy, David M. Walsh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: David M. Walsh
Context triple: [Seems Like Old Times, cinematographyBy, David M. Walsh]
  • A. David M. Walsh chosen
    David M. Walsh is an American cinematographer known for his work on numerous films, particularly comedies, during the 1970s and 1980s.
  • B. David Walsh
    David Walsh is an Australian professional gambler, art collector, and entrepreneur best known as the founder of Hobart’s provocative Museum of Old and New Art (MONA).
  • C. Gerard A. Buccafusco
    Gerard A. Buccafusco is a local political figure who has served as the mayor of Belmar, New Jersey.
  • D. Kevin J. Walsh
    Kevin J. Walsh is a film producer known for his work on major Hollywood productions, including the 2022 adaptation of "Death on the Nile."
  • E. Michael H. Moloney
    Michael H. Moloney is a physics-focused science policy and leadership professional who serves as the chief executive officer of the American Institute of Physics.
  • 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_69c68a59f2288190877ca15c19b1e822 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f10e71fc81909307ca39a61142d3 completed March 27, 2026, 9:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8fa20137081909a21ac366c19407f completed March 29, 2026, 10:08 a.m.
Created at: March 27, 2026, 3:05 p.m.