Triple

T15926668
Position Surface form Disambiguated ID Type / Status
Subject MTV Movie Award for Best Villain E386220 entity
Predicate notableWinner P2766 FINISHED
Object Josh Brolin E69966 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: Josh Brolin | Statement: [MTV Movie Award for Best Villain, notableWinner, Josh Brolin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Josh Brolin
Context triple: [MTV Movie Award for Best Villain, notableWinner, Josh Brolin]
  • A. Josh Brolin chosen
    Josh Brolin is an American actor known for his versatile performances in films such as "No Country for Old Men," "W." and for portraying Thanos in the Marvel Cinematic Universe.
  • B. Ben Foster
    Ben Foster is an American actor known for his intense, often gritty performances in films such as "3:10 to Yuma," "Hell or High Water," and "The Messenger."
  • C. Ben Foster
    Ben Foster is a British composer and orchestrator best known for his work on television scores, including contributions to the revived Doctor Who series.
  • D. Anthony Redman
    Anthony Redman is a film editor best known for his work on the 1990 crime drama "King of New York."
  • E. Michael Bell
    Michael Bell is an American voice actor known for his extensive work in animated television series, films, and video games since the 1970s.
  • 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_69d86da750008190987eb26be3f6c118 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e156866de48190a744e8dcaa0c66f1 completed April 16, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffb5adcde88190ae2a845aaa9d31ac completed May 9, 2026, 10:31 p.m.
Created at: April 10, 2026, 4:52 a.m.