Triple

T5042047
Position Surface form Disambiguated ID Type / Status
Subject The Asphalt Jungle E113566 entity
Predicate castMember P1668 FINISHED
Object Brad Dexter E269554 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: Brad Dexter | Statement: [The Asphalt Jungle, castMember, Brad Dexter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brad Dexter
Context triple: [The Asphalt Jungle, castMember, Brad Dexter]
  • A. Brad Dexter chosen
    Brad Dexter was an American character actor and film producer best known for his role as one of the gunfighters in the classic Western film "The Magnificent Seven."
  • B. Jeffrey Dean
    Jeffrey Dean is a prominent American computer scientist and software engineer best known for his influential work on large-scale distributed systems and infrastructure at Google.
  • C. Stephen Garrett
    Stephen Garrett is a British television and film producer best known as the co-founder and former executive chairman of the production company Kudos, behind acclaimed series such as "Spooks" and "Life on Mars."
  • D. Tim Mahoney
    Tim Mahoney is an American musician best known as the lead guitarist for the rock band 311.
  • E. Luke Goss
    Luke Goss is an English actor and former drummer best known for his roles in genre films such as "Blade II" and "Hellboy II: The Golden Army."
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73de73008190b89aec9a76b43e4f completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb0f21d308190adbac06397f90cee completed March 21, 2026, 2:53 p.m.
Created at: March 20, 2026, 1:37 p.m.