Triple

T13071960
Position Surface form Disambiguated ID Type / Status
Subject Entrapment E329478 entity
Predicate starring P1507 FINISHED
Object Maury Chaykin E477639 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: Maury Chaykin | Statement: [Entrapment, starring, Maury Chaykin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maury Chaykin
Context triple: [Entrapment, starring, Maury Chaykin]
  • A. Maury Chaykin chosen
    Maury Chaykin was a Canadian-American character actor known for his memorable supporting roles in film and television, including his acclaimed portrayal of detective Nero Wolfe in the TV series "A Nero Wolfe Mystery."
  • B. Glenn Gilger
    Glenn Gilger is an American child voice actor best known for providing the voice of one of the Peanuts characters in the animated film "A Boy Named Charlie Brown."
  • C. Louis Begley
    Louis Begley is a Polish-born American novelist and lawyer best known for his critically acclaimed works exploring identity, morality, and the legacy of the Holocaust.
  • D. Stephen Macht
    Stephen Macht is an American actor known for his work in film and television, including prominent roles in horror and crime dramas.
  • E. Stacy Keach
    Stacy Keach is an American actor known for his powerful character roles in film, television, and theater, often portraying tough, authoritative figures.
  • 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_69d80771749c81909a6d9197b9504872 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980ee6130819095d835e7ff6a8c5b completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f71f0ff20081909f277d9c8dc8b043 completed May 3, 2026, 10:10 a.m.
Created at: April 9, 2026, 9 p.m.