Triple

T21282074
Position Surface form Disambiguated ID Type / Status
Subject Russell Rouse E524550 entity
Predicate notableWork P4 FINISHED
Object The Thief 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: The Thief | Statement: [Russell Rouse, notableWork, The Thief]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Thief
Context triple: [Russell Rouse, notableWork, The Thief]
  • A. The Thief chosen
    The Thief is a 1952 American film noir notable for its nearly wordless storytelling and tense Cold War espionage plot.
  • B. The Thief
    The Thief is a notable work by George Alexander, likely a crime- or mystery-themed story centered on theft and moral ambiguity.
  • C. Honest Thief
    Honest Thief is a 2020 action-thriller film starring Liam Neeson as a reformed bank robber who becomes the target of corrupt FBI agents after trying to turn himself in.
  • D. The Good Thief
    The Good Thief is a 2002 crime drama film directed by Neil Jordan that follows an aging gambler and thief attempting one last elaborate heist on the French Riviera.
  • E. Once a Thief
    Once a Thief is a 1991 Hong Kong action-comedy film blending heist capers with stylized gunplay and humor.
  • 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_69e0b5171f6c8190a5d57201ede73811 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e736d249fc8190b0b310467ddeac3c completed April 21, 2026, 8:35 a.m.
Created at: April 16, 2026, 4:02 p.m.