Triple

T5587523
Position Surface form Disambiguated ID Type / Status
Subject Kill Bill: Volume 2 E146791 entity
Predicate starring 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: [Kill Bill: Volume 2, starring, Uma Thurman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uma Thurman
Context triple: [Kill Bill: Volume 2, starring, 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c0209d713081908b39ee8befb2faf7 completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0286558b48190a8907c06111a48f3 completed March 22, 2026, 5:35 p.m.
Created at: March 22, 2026, 3:38 p.m.