Triple

T12224972
Position Surface form Disambiguated ID Type / Status
Subject The Sword of Ali Baba E291324 entity
Predicate castMember P1668 FINISHED
Object John Crawford E489003 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: John Crawford | Statement: [The Sword of Ali Baba, castMember, John Crawford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Crawford
Context triple: [The Sword of Ali Baba, castMember, John Crawford]
  • A. John Crawford chosen
    John Crawford was an American character actor known for his numerous supporting roles in film and television from the 1940s through the 1980s.
  • B. Gary Starkweather
    Gary Starkweather was an American engineer and inventor best known for creating the laser printer while working at Xerox.
  • C. William Holmes
    William Holmes was a film editor best known for his Academy Award-winning work on the 1941 biographical war film "Sergeant York."
  • D. Michael Martin
    Michael Martin was a British Labour politician who served as Speaker of the House of Commons in the early 21st century and was later created Baron Martin of Springburn.
  • E. Aaron McKinney
    Aaron McKinney is an American man best known as one of the two assailants convicted in the 1998 murder of Matthew Shepard, a crime that drew national attention to anti-LGBTQ+ hate violence.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91ca11f788190bad2efb6c83ffccb completed April 10, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aa9023881909f8373e02d2cad4b completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:51 p.m.