Triple

T11385852
Position Surface form Disambiguated ID Type / Status
Subject Granny E269712 entity
Predicate voicedInVariousWorksBy P83203 FINISHED
Object Bob Bergen E269748 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: Bob Bergen | Statement: [Granny, voicedInVariousWorksBy, Bob Bergen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bob Bergen
Context triple: [Granny, voicedInVariousWorksBy, Bob Bergen]
  • A. Bob Bergen chosen
    Bob Bergen is an American voice actor best known for voicing classic Looney Tunes characters, including Porky Pig and Marvin the Martian.
  • B. Jon Bokenkamp
    Jon Bokenkamp is an American screenwriter and producer best known for creating the television series "The Blacklist" and writing several thriller films.
  • C. Bob Peterson
    Bob Peterson is an American animator, screenwriter, and voice actor at Pixar best known for co-directing "Up" and voicing characters such as Dug the dog.
  • D. Steve Shagan
    Steve Shagan was an American novelist, screenwriter, and producer best known for his Academy Award–nominated work on socially conscious films of the 1970s.
  • E. Jon Berg
    Jon Berg is a film producer and studio executive known for his work on major Hollywood blockbusters, including several DC Extended Universe films.
  • 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_69d6aacdbc6c8190af6dc3d5f5d22836 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d808855a7481909314f90ad92aae68 completed April 9, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e58c3c9a7081908002d726ec9e7715 completed April 20, 2026, 2:15 a.m.
Created at: April 8, 2026, 9:34 p.m.