Triple

T20236813
Position Surface form Disambiguated ID Type / Status
Subject Jill Arlyn Oppenheim E498170 entity
Predicate appearedIn P795 FINISHED
Object The Oscar NE NERFINISHED

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: The Oscar | Statement: [Jill Arlyn Oppenheim, appearedIn, The Oscar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Oscar
Context triple: [Jill Arlyn Oppenheim, appearedIn, The Oscar]
  • A. The Oscar chosen
    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.
  • B. Milla de Oro
    Milla de Oro is the main financial and commercial district of San Juan, Puerto Rico, known for its concentration of banks, corporate offices, and upscale developments.
  • C. Oscar
    Oscar is the NATO reporting name for a class of large, nuclear-powered guided-missile submarines originally built by the Soviet Navy and now operated by the Russian Navy.
  • D. 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.
  • E. Oscar
    Oscar is a masculine given name of Old English and Norse origin, commonly used in many European and English-speaking countries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6274c58c81909c646eabed6f4f30 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6716a5af0819095ea419a4d1f0d1d completed April 20, 2026, 6:33 p.m.
Created at: April 11, 2026, 11:40 p.m.