Triple

T17830302
Position Surface form Disambiguated ID Type / Status
Subject Linda Harrison E445234 entity
Predicate appearedIn P795 FINISHED
Object The Fat Spy — 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 Fat Spy | Statement: [Linda Harrison, appearedIn, The Fat Spy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: The Fat Spy
Context triple: [Linda Harrison, appearedIn, The Fat Spy]
  • A. The Fat Spy chosen
    The Fat Spy is a 1966 American musical comedy film that parodies beach party movies, featuring a cast including Phyllis Diller and Jack E. Leonard.
  • B. The Spy
    "The Spy" is an 1821 historical novel by James Fenimore Cooper set during the American Revolutionary War, often regarded as one of the earliest major works of American fiction.
  • C. The Spy
    The Spy is a film featuring Russian actress Svetlana Khodchenkova in a prominent role within a Cold War espionage narrative.
  • D. My Spy
    My Spy is a 2020 action-comedy film in which Dave Bautista plays a tough CIA operative who unexpectedly becomes the guardian and mentor of a precocious young girl.
  • E. I Was a Spy
    I Was a Spy is a 1933 British war drama film about a Belgian woman who becomes a spy during World War I.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48917c4d88190b919a4b75aed011c completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.