Triple

T10946862
Position Surface form Disambiguated ID Type / Status
Subject Kevin Hart: Let Me Explain E258620 entity
Predicate director P255 FINISHED
Object Leslie Small E889266 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: Leslie Small | Statement: [Kevin Hart: Let Me Explain, director, Leslie Small]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leslie Small
Context triple: [Kevin Hart: Let Me Explain, director, Leslie Small]
  • A. Leslie Small chosen
    Leslie Small is an American film and television director best known for helming numerous stand-up comedy specials, including several for comedian Kevin Hart.
  • B. Leslie Frost
    Leslie Frost was a Canadian politician who served as the 16th Premier of Ontario from 1949 to 1961.
  • C. Leslie Hunter
    Leslie Hunter is one of the central young adult characters in the 1985 coming-of-age film "St. Elmo's Fire," navigating post-college relationships and personal ambitions.
  • D. Leslie Harter
    Leslie Harter is a film producer known for her work in Hollywood and for being married to director Robert Zemeckis.
  • E. Leslie Fenton
    Leslie Fenton was a British-born American actor and film director active in Hollywood during the early to mid-20th century.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770eaaea08190b06e508600d8a305 completed April 9, 2026, 9:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d733f7d88190b45df5c155ff5a46 completed April 18, 2026, 12:58 a.m.
Created at: April 8, 2026, 9:23 p.m.