Triple

T14710096
Position Surface form Disambiguated ID Type / Status
Subject The Muppet Movie E345525 entity
Predicate writer P1360 FINISHED
Object Jerry Juhl E363719 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: Jerry Juhl | Statement: [The Muppet Movie, writer, Jerry Juhl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerry Juhl
Context triple: [The Muppet Movie, writer, Jerry Juhl]
  • A. Jerry Juhl chosen
    Jerry Juhl was an American screenwriter best known as the head writer for Jim Henson’s Muppets, contributing to projects like The Muppet Show and several Muppet films.
  • B. Duane Schuler
    Duane Schuler is an American theatrical lighting designer known for his work in opera, including major productions at leading opera houses.
  • C. Dan Pfeiffer
    Dan Pfeiffer is an American political strategist and former White House communications director who served as a senior adviser to President Barack Obama.
  • D. John Diehl
    John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
  • E. Fred Schuler
    Fred Schuler is a cinematographer best known for his work on films such as the 1980 comedy "Stir Crazy."
  • 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_69d822e4a8c08190a155df736bb7bc13 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb9814e0c8190984ac30d276499cc completed April 14, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd1de868819084d71f75210d14f5 completed May 9, 2026, 7:07 a.m.
Created at: April 10, 2026, 1:28 a.m.