Triple

T14213147
Position Surface form Disambiguated ID Type / Status
Subject Whip It E352280 entity
Predicate castMember P1668 FINISHED
Object Kristen Wiig E67174 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: Kristen Wiig | Statement: [Whip It, castMember, Kristen Wiig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kristen Wiig
Context triple: [Whip It, castMember, Kristen Wiig]
  • A. Kristen Wiig chosen
    Kristen Wiig is an American comedian, actress, and writer best known for her work on Saturday Night Live and films such as Bridesmaids.
  • B. Melissa McCarthy
    Melissa McCarthy is an American actress and comedian known for her breakout comedic role in "Bridesmaids" and subsequent work in film and television.
  • C. Maya Rudolph
    Maya Rudolph is an American actress and comedian known for her work on "Saturday Night Live" and in numerous film and animated voice roles.
  • D. Amy Poehler
    Amy Poehler is an American comedian, actress, writer, and producer best known for her work on "Saturday Night Live" and for starring as Leslie Knope on the sitcom "Parks and Recreation."
  • E. Tina Fey
    Tina Fey is an American comedian, writer, actress, and producer best known for her work on "Saturday Night Live" and creating the acclaimed sitcom "30 Rock."
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de620f07bc81909212dcd1c91b5f95 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe249ebd3c81908d8b562845d9ceb1 completed May 8, 2026, 5:59 p.m.
Created at: April 10, 2026, 1:06 a.m.