Triple

T12877415
Position Surface form Disambiguated ID Type / Status
Subject Red Heat E308003 entity
Predicate castMember P1668 FINISHED
Object Peter Boyle E162392 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: Peter Boyle | Statement: [Red Heat, castMember, Peter Boyle]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Boyle
Context triple: [Red Heat, castMember, Peter Boyle]
  • A. Peter Boyle chosen
    Peter Boyle was an American character actor best known for his roles in films like "Young Frankenstein" and "Taxi Driver" and the TV series "Everybody Loves Raymond."
  • B. Peter Boyle
    Peter Boyle is a film editor known for his work on acclaimed movies such as "The Hours."
  • C. Harold Gould
    Harold Gould was an American character actor best known for his prolific work in film and television from the 1960s through the 1990s, including memorable roles in projects like "The Sting" and the TV series "The Golden Girls."
  • D. Robert Walter
    Robert Walter is a British Conservative politician who served as a Member of Parliament, notably representing the North Dorset constituency for many years.
  • E. Alan Baxter
    Alan Baxter was an American character actor known for his roles in mid-20th-century film and television, often portraying tough or villainous 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_69d7bdf69bc48190af6c2621f28ca351 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d970fa8474819086a8af3c90f3ca84 completed April 10, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ef4ba8819099335d155feb01d9 completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 5:38 p.m.