Triple

T11338596
Position Surface form Disambiguated ID Type / Status
Subject John Green E268535 entity
Predicate influencedBy P9 FINISHED
Object Kurt Vonnegut E233850 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: Kurt Vonnegut | Statement: [John Green, influencedBy, Kurt Vonnegut]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kurt Vonnegut
Context triple: [John Green, influencedBy, Kurt Vonnegut]
  • A. Kurt Vonnegut chosen
    Kurt Vonnegut was an American novelist and satirist known for his darkly humorous, genre-blending works such as "Slaughterhouse-Five" and "Cat's Cradle."
  • B. Mark Vonnegut
    Mark Vonnegut is an American pediatrician and memoirist known for writing about his experiences with mental illness and for being the son of author Kurt Vonnegut.
  • C. Joseph Heller
    Joseph Heller was an American novelist and satirist best known for his darkly comic World War II novel "Catch-22."
  • D. Thomas Pynchon
    Thomas Pynchon is a reclusive American novelist known for his dense, complex, and postmodern works such as "Gravity’s Rainbow" and "The Crying of Lot 49."
  • E. William Gaddis
    William Gaddis was an American postmodern novelist known for his dense, allusive, and formally experimental works such as "The Recognitions" and "JR."
  • 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_69d6aacb1f0881908c84a349fd1be047 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7ea008b5081908e6c6c6fc29ef936 completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5433d3e848190ad4f51c23d5a8bb2 completed April 19, 2026, 9:03 p.m.
Created at: April 8, 2026, 9:33 p.m.