Triple

T8020102
Position Surface form Disambiguated ID Type / Status
Subject Beautiful Girls E186717 entity
Predicate portrayedBy P1507 FINISHED
Object Uma Thurman E290199 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: Uma Thurman | Statement: [Beautiful Girls, portrayedBy, Uma Thurman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uma Thurman
Context triple: [Beautiful Girls, portrayedBy, Uma Thurman]
  • A. Uma Thurman chosen
    Uma Thurman is an American actress and model best known for her roles in films such as "Pulp Fiction" and the "Kill Bill" series.
  • B. Gina Gershon
    Gina Gershon is an American actress known for her versatile roles in film, television, and theater, including standout performances in movies like "Bound" and "Showgirls."
  • C. Jennifer Jason Leigh
    Jennifer Jason Leigh is an American actress known for her intense, character-driven performances in films such as "Fast Times at Ridgemont High," "Single White Female," and "The Hateful Eight."
  • D. Famke Janssen
    Famke Janssen is a Dutch actress and former fashion model best known for her roles in the X-Men film series and the James Bond film GoldenEye.
  • E. Andie MacDowell
    Andie MacDowell is an American actress and former fashion model best known for her roles in romantic comedies such as "Groundhog Day" and "Four Weddings and a Funeral."
  • 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_69ca82ac7fc081909b1398cf025423af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3e8bc90081909f6f5878e6f1f241 completed March 31, 2026, 3:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56c82824819082e93eddc40bfad1 completed March 31, 2026, 11:20 p.m.
Created at: March 30, 2026, 5:20 p.m.