Triple

T11318312
Position Surface form Disambiguated ID Type / Status
Subject Nathaniel Benchley E268023 entity
Predicate name P16 FINISHED
Object Nathaniel Benchley E268023 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: Nathaniel Benchley | Statement: [Nathaniel Benchley, name, Nathaniel Benchley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nathaniel Benchley
Context triple: [Nathaniel Benchley, name, Nathaniel Benchley]
  • A. Nathaniel Benchley chosen
    Nathaniel Benchley was an American author and screenwriter known for his humorous novels and stories, several of which were adapted into popular films.
  • B. Peter Benchley
    Peter Benchley was an American author and screenwriter best known for writing the novel "Jaws," which was adapted into the iconic 1975 film.
  • C. Peter Heller
    Peter Heller is a British DJ, remixer, and record producer best known for his influential work in house music during the 1990s and 2000s.
  • D. Barry Lopez
    Barry Lopez was an acclaimed American author and essayist best known for his nature writing and explorations of human relationships with the environment, particularly in works like "Arctic Dreams" and "Of Wolves and Men."
  • E. Paul Sawtell
    Paul Sawtell was a prolific film composer known for scoring numerous Hollywood genre films, particularly in science fiction and horror, during the mid-20th century.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9de875481908acfa56015d4b46f completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e542f294988190bb456326e4184dcb completed April 19, 2026, 9:02 p.m.
Created at: April 8, 2026, 9:32 p.m.