Triple

T14751364
Position Surface form Disambiguated ID Type / Status
Subject Candyman: Farewell to the Flesh E346614 entity
Predicate castMember P1668 FINISHED
Object Matt Clark E513657 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: Matt Clark | Statement: [Candyman: Farewell to the Flesh, castMember, Matt Clark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Clark
Context triple: [Candyman: Farewell to the Flesh, castMember, Matt Clark]
  • A. Matt Clark chosen
    Matt Clark was an American character actor known for his numerous supporting roles in Westerns and other films and television series from the 1960s onward.
  • B. Todd Clark
    Todd Clark is a Canadian songwriter and record producer known for his work with various pop and country artists.
  • C. Dane Clark
    Dane Clark was an American film and television actor known for his tough, working-class persona in numerous 1940s and 1950s Hollywood dramas and war movies.
  • D. Mike E. Clark
    Mike E. Clark is an American record producer best known for his long-running work with Insane Clown Posse and other artists on the Psychopathic Records label.
  • E. Les Clark
    Les Clark was an American animator and one of Disney’s famed "Nine Old Men," known for his influential work on many classic Disney films.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec7d40efc8190bb1be34c19a2b57c completed April 14, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb9a56a08190b6a178cd930a072d completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:30 a.m.