Triple

T3785097
Position Surface form Disambiguated ID Type / Status
Subject The Opposite of Sex E85511 entity
Predicate producer P490 FINISHED
Object Ralph Winter E377151 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: Ralph Winter | Statement: [The Opposite of Sex, producer, Ralph Winter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ralph Winter
Context triple: [The Opposite of Sex, producer, Ralph Winter]
  • A. Ralph Winter chosen
    Ralph Winter is an American film producer best known for his work on major genre franchises such as the X-Men series and the Star Trek films.
  • B. Ralph Arnold
    Ralph Arnold is the name of several notable individuals, including figures in fields such as geology, engineering, and the arts.
  • C. Ralph Hart
    Ralph Hart is an actor best known for his role on the classic American television sitcom "The Lucy Show."
  • D. Ralph Miller
    Ralph Miller was a highly respected American college basketball coach best known for transforming Oregon State University into a national contender during his long tenure.
  • E. Jerry Wald
    Jerry Wald was an American film producer and screenwriter known for his influential work in Hollywood during the 1930s–1950s, including several acclaimed dramas and film noirs.
  • 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_69aed937fa8881908208ef3801060826 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aee3dd80f08190a1704521a764e22c completed March 9, 2026, 3:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5282f253c81908c18a30bb1025f99 completed March 14, 2026, 9:19 a.m.
Created at: March 9, 2026, 3:13 p.m.