Triple

T20103945
Position Surface form Disambiguated ID Type / Status
Subject Money Train E496618 entity
Predicate editedBy P1954 FINISHED
Object George Bowers NE NERFINISHED

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: George Bowers | Statement: [Money Train, editedBy, George Bowers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Bowers
Context triple: [Money Train, editedBy, George Bowers]
  • A. George Bowers chosen
    George Bowers was an American film editor known for his work on numerous Hollywood movies, including the baseball comedy-drama "A League of Their Own."
  • B. William Bowers
    William Bowers was an American screenwriter known for his sharp, witty scripts in mid-20th-century Hollywood crime films and comedies.
  • C. Charles W. Bowers
    Charles W. Bowers was a prominent Orange County civic leader and philanthropist whose legacy is commemorated by the Bowers Museum in Santa Ana, California.
  • D. Richard Bower
    Richard Bower was a 16th-century English musician and court official who directed and trained the boy choristers of the Chapel Royal under the Tudor monarchs.
  • E. Richard Burrell
    Richard Burrell is a British television producer best known for his work as an executive producer on the long-running BBC crime drama series "New Tricks."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e666daf73c819089f02ca6faa2c283 completed April 20, 2026, 5:48 p.m.
Created at: April 11, 2026, 11:27 p.m.