Triple

T10036738
Position Surface form Disambiguated ID Type / Status
Subject Larisa Shepitko E205188 entity
Predicate awardReceived P11 FINISHED
Object Golden Bear E70477 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: Golden Bear | Statement: [Larisa Shepitko, awardReceived, Golden Bear]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Golden Bear
Context triple: [Larisa Shepitko, awardReceived, Golden Bear]
  • A. Golden Bear
    Golden Bear is the mascot representing Western New England University’s athletic teams and school spirit.
  • B. Golden Bear chosen
    The Golden Bear is the top prize awarded to the best film at the prestigious Berlin International Film Festival, one of the world’s major annual film festivals.
  • C. Golden Lion
    The Golden Lion is the top prize awarded for the best film at the prestigious Venice Film Festival.
  • D. The Oscar
    The Oscar is a 1966 American drama film about the ruthless rise and moral downfall of a Hollywood actor, noted for its melodramatic portrayal of the film industry.
  • E. Oscar
    The Oscar is a prestigious film industry award presented annually by the Academy of Motion Picture Arts and Sciences to honor outstanding cinematic achievements.
  • 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_69ca834f70e88190b2d74828b7767ec1 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdce4bb3408190ac5dae4718ef7cad completed April 2, 2026, 2:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69d28258ab088190a31ad5854d91193b completed April 5, 2026, 3:40 p.m.
Created at: March 30, 2026, 8:55 p.m.