Triple

T17444368
Position Surface form Disambiguated ID Type / Status
Subject Le Mat E424741 entity
Predicate usedBy P260 FINISHED
Object Paul Le Mat 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: Paul Le Mat | Statement: [Le Mat, usedBy, Paul Le Mat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Le Mat
Context triple: [Le Mat, usedBy, Paul Le Mat]
  • A. Paul Le Mat chosen
    Paul Le Mat is an American actor best known for his breakout role as the hot-rodder John Milner in the coming-of-age film "American Graffiti."
  • B. John Saul
    John Saul was a male prostitute in late 19th-century London whose involvement in the 1889 Cleveland Street scandal linked him to a high-profile case of homosexual activity and social controversy in Victorian Britain.
  • C. Raoul Le Mat
    Raoul Le Mat was a French-born film director and ice hockey enthusiast who played a key role in establishing and promoting ice hockey in Sweden in the early 20th century.
  • D. Ken Burrough
    Ken Burrough was an American professional football wide receiver best known for his Pro Bowl career with the Houston Oilers in the 1970s.
  • E. Paul Briggs
    Paul Briggs is an American animator, storyboard artist, and voice actor best known for his work on Disney animated films such as Frozen and Big Hero 6.
  • 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_69d889db0ba481908402409af3b37917 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e44ffa2d84819086474649eba1065c completed April 19, 2026, 3:46 a.m.
Created at: April 10, 2026, 5:47 a.m.