Triple

T1198278
Position Surface form Disambiguated ID Type / Status
Subject Edge of Tomorrow E25717 entity
Predicate castMember P1668 FINISHED
Object Bill Paxton E81453 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: Bill Paxton | Statement: [Edge of Tomorrow, castMember, Bill Paxton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Paxton
Context triple: [Edge of Tomorrow, castMember, Bill Paxton]
  • A. Bill Paxton chosen
    Bill Paxton was an American actor and filmmaker known for his versatile roles in films such as "Aliens," "Twister," "Titanic," and "Apollo 13."
  • B. Jeff Bridges
    Jeff Bridges is an acclaimed American actor known for his versatile performances in films such as "The Big Lebowski," "Crazy Heart," and "True Grit."
  • C. John Goodman
    John Goodman is an American actor known for his roles in the sitcom "Roseanne," numerous Coen brothers films, and for voicing Sulley in Pixar's "Monsters, Inc." franchise.
  • D. Danny Glover
    Danny Glover is an American actor and activist best known for his roles in films such as the "Lethal Weapon" series and "The Color Purple."
  • E. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • 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_69a49429f5ec8190a6a205eb0ae81e5e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd9c013c8190822d44d465d60fdb completed March 1, 2026, 10:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac831703bc8190839deb02075cb8fd completed March 7, 2026, 7:57 p.m.
Created at: March 1, 2026, 7:46 p.m.