Triple

T5349513
Position Surface form Disambiguated ID Type / Status
Subject The Opposite Sex E124140 entity
Predicate producer P490 FINISHED
Object Joe Pasternak E117706 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: Joe Pasternak | Statement: [The Opposite Sex, producer, Joe Pasternak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joe Pasternak
Context triple: [The Opposite Sex, producer, Joe Pasternak]
  • A. Joe Pasternak chosen
    Joe Pasternak was a prominent Hollywood film producer best known for his successful musicals and light comedies from the 1930s through the 1950s.
  • B. Peter Pasternak
    Peter Pasternak is known primarily as the son of famed Hollywood film producer Joe Pasternak.
  • C. Boris Pasternak
    Boris Pasternak was a Russian poet and novelist best known internationally for his novel "Doctor Zhivago," which earned him the Nobel Prize in Literature in 1958.
  • D. Leonid Pasternak
    Leonid Pasternak was a Russian Impressionist painter and illustrator known for his portraits and his association with the literary and artistic circles of late Imperial Russia.
  • E. Joseph Brodsky
    Joseph Brodsky was a Russian-American poet and essayist, Nobel laureate, and former Soviet dissident whose work blends metaphysical reflection, formal rigor, and exile experience.
  • 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_69bd464be27081908807b40b75c1bbae completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd860ea7088190ad7be14132927d17 completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21d0d4d08190a33c86553d2012fa completed March 21, 2026, 10:55 p.m.
Created at: March 20, 2026, 2:01 p.m.