Triple

T12108343
Position Surface form Disambiguated ID Type / Status
Subject Peyton Place E288359 entity
Predicate screenwriter P2831 FINISHED
Object John Michael Hayes E302114 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: John Michael Hayes | Statement: [Peyton Place, screenwriter, John Michael Hayes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Michael Hayes
Context triple: [Peyton Place, screenwriter, John Michael Hayes]
  • A. John Michael Hayes chosen
    John Michael Hayes was an American screenwriter best known for his collaborations with Alfred Hitchcock, including writing the screenplay for "Rear Window."
  • B. David Hayes
    David Hayes is an American music industry figure best known as the co-founder of the influential punk label Lookout! Records.
  • C. John Hayes
    John Hayes is a technology entrepreneur best known as a co-founder of the data storage company Pure Storage.
  • D. Peter Hayes
    Peter Hayes is a British diplomat and civil servant who has served in senior roles including Commissioner of the British Antarctic Territory.
  • E. Gregory J. Hayes
    Gregory J. Hayes is an American business executive best known for leading major aerospace and defense companies, including serving as CEO of RTX (formerly Raytheon Technologies).
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915632dc48190863e0239cef37e24 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f67b3f2c8190bcb2120781f91220 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:49 p.m.