Triple

T22965338
Position Surface form Disambiguated ID Type / Status
Subject Jim Morris E571026 entity
Predicate name P16 FINISHED
Object Jim Morris NE NERFINISHED

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: Jim Morris | Statement: [Jim Morris, name, Jim Morris]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jim Morris
Context triple: [Jim Morris, name, Jim Morris]
  • A. Jim Morris chosen
    Jim Morris is an American film producer and executive best known for his work at Pixar Animation Studios, including producing the acclaimed animated film WALL-E.
  • B. Jim Morris
    Jim Morris is a high school teacher and former baseball pitcher whose unlikely late-career rise to the major leagues inspired the film "The Rookie."
  • C. Jeff Morris
    Jeff Morris was an American character actor best known for his supporting roles in films and television from the 1960s through the 1980s, including a memorable appearance in the war comedy "Kelly's Heroes."
  • D. Brian Morris
    Brian Morris is an American jurist who serves as the Chief Judge of the United States District Court for the District of Montana and is known for his federal judicial service in that state.
  • E. Bruce Morris
    Bruce Morris is an American screenwriter and storyboard artist known for his work on animated films, including contributions to Disney projects.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245b2c6548190a0e4c7f2f7df2d48 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1822e542c8190a865f18e64fc0768 completed April 29, 2026, 3:59 a.m.
Created at: April 17, 2026, 3:47 p.m.