Triple

T17018413
Position Surface form Disambiguated ID Type / Status
Subject Duck Butter E412880 entity
Predicate castMember P1668 FINISHED
Object Kate Berlant E257168 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: Kate Berlant | Statement: [Duck Butter, castMember, Kate Berlant]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Berlant
Context triple: [Duck Butter, castMember, Kate Berlant]
  • A. Kate Berlant chosen
    Kate Berlant is an American comedian and actress known for her surreal, improvisational stand-up and roles in projects like the series "A League of Their Own" and the film "Sorry to Bother You."
  • B. Molly Gordon
    Molly Gordon is an American actress and director known for her roles in films like "Booksmart" and "Good Boys" and the TV series "The Bear."
  • C. Edie Mirman
    Edie Mirman is an American voice actress known for her work in animation and dubbing, including roles in popular films and television series.
  • D. Kate Beringer
    Kate Beringer is a key protagonist in the 1984 horror-comedy film "Gremlins," known for her resourcefulness and courage in battling the mischievous creatures overrunning her town.
  • E. Lily Schechner
    Lily Schechner is the teenage protagonist and aspiring witch at the center of the supernatural coming-of-age story in the film "The Craft: Legacy."
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d480a58c8190a3912d26debb4311 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4d6cb881909b64b4368fd97fa9 completed May 10, 2026, 11:57 p.m.
Created at: April 10, 2026, 5:33 a.m.