Triple

T5588846
Position Surface form Disambiguated ID Type / Status
Subject Air Bud E146825 entity
Predicate cinematographyBy P1953 FINISHED
Object Mike Southon E178938 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: Mike Southon | Statement: [Air Bud, cinematographyBy, Mike Southon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mike Southon
Context triple: [Air Bud, cinematographyBy, Mike Southon]
  • A. Mike Southon chosen
    Mike Southon is a British cinematographer known for his work on feature films, television, and commercials.
  • B. Paul Bigot
    Paul Bigot was a French architect best known for creating the detailed plaster "Plan de Rome," a large-scale model reconstructing ancient Rome.
  • C. Anthony Veiller
    Anthony Veiller was an American screenwriter known for his work on notable mid-20th-century films, including several acclaimed Hollywood dramas and thrillers.
  • D. Charles LeMaire
    Charles LeMaire was an American costume designer renowned for his work in Hollywood’s Golden Age, earning multiple Academy Awards for his contributions to classic films.
  • E. Ian La Frenais
    Ian La Frenais is a British screenwriter best known for co-creating classic TV comedies such as "Porridge" and "Auf Wiedersehen, Pet," and for his long-time writing partnership with Dick Clement.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0209e892c8190b936a05ef2a14d36 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059fc908c819087eb9b81fedffb4f completed March 22, 2026, 9:07 p.m.
Created at: March 22, 2026, 3:38 p.m.