Triple

T14455331
Position Surface form Disambiguated ID Type / Status
Subject A Mighty Wind E358443 entity
Predicate producer P490 FINISHED
Object Karen Murphy E1138195 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: Karen Murphy | Statement: [A Mighty Wind, producer, Karen Murphy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karen Murphy
Context triple: [A Mighty Wind, producer, Karen Murphy]
  • A. Karen Murphy chosen
    Karen Murphy is a film producer known for her work on the acclaimed mockumentary comedy "Best in Show."
  • B. Katherine Murphy
    Katherine Murphy is a central character in the romantic comedy film "Just Go with It," where she becomes entangled in a web of lies and pretend relationships that evolve into genuine romance.
  • C. Colleen Murphy
    Colleen Murphy is a Canadian playwright, filmmaker, and librettist renowned for her powerful, emotionally intense stage works.
  • D. Rosemary Murphy
    Rosemary Murphy was an American character actress known for her work in film, television, and theater, including roles in productions such as "To Kill a Mockingbird" and numerous stage performances.
  • E. Karen Cunningham
    Karen Cunningham is known as the spouse of Ward Cunningham, the American computer programmer who created the first wiki.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91a8bf088190abf5fd4f646b8c62 completed April 14, 2026, 7:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb75ea708190a30153c76cde8e79 completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 1:19 a.m.