Triple

T7256974
Position Surface form Disambiguated ID Type / Status
Subject History of the World, Part I E157745 entity
Predicate cinematographyBy P1953 FINISHED
Object Woody Omens E248302 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: Woody Omens | Statement: [History of the World, Part I, cinematographyBy, Woody Omens]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Woody Omens
Context triple: [History of the World, Part I, cinematographyBy, Woody Omens]
  • A. Woody Omens chosen
    Woody Omens is an American cinematographer best known for his work on films such as the 1989 crime-comedy "Harlem Nights."
  • B. Woopi
    Woopi is the colloquial nickname for Woolgoolga, a coastal town in New South Wales, Australia known for its beaches and large Sikh community.
  • C. Woody
    Woody is the commonly used nickname of American businessman and New York Jets owner Woody Johnson.
  • D. Woody
    Woody is the nickname of Woody Guthrie, the influential American folk singer-songwriter known for his protest music and the anthem "This Land Is Your Land."
  • E. Wishbone
    Wishbone is a mobile social networking app that lets users compare and vote between two options in quick, image-based polls.
  • 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_69c6882d81d4819085f7ff862951ee4f completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6eaa274bc8190b017b71583711453 completed March 27, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7d3b541708190b66233813b167453 completed March 28, 2026, 1:12 p.m.
Created at: March 27, 2026, 2:57 p.m.