Triple

T765315
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best International Feature Film E16161 entity
Predicate hasLanguageFocus P8383 FINISHED
Object non-English-language cinema LITERAL 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: non-English-language cinema | Statement: [Academy Award for Best International Feature Film, hasLanguageFocus, non-English-language cinema]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLanguageFocus
Context triple: [Academy Award for Best International Feature Film, hasLanguageFocus, non-English-language cinema]
  • A. hasPrimaryFocus
    Indicates that something is the main subject, concern, or area of attention for an entity or activity.
  • B. hasCollectionFocus
    Indicates that something is primarily concerned with, centered on, or directed toward a particular collection or set of items.
  • C. hasLanguageContext chosen
    Indicates that an entity is associated with or interpreted within a specific language or linguistic context.
  • D. mayProvideFocus
    Indicates that one entity can potentially direct attention, emphasis, or concentration toward another entity or aspect.
  • E. hasLanguageOn
    Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
  • F. None of above.

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_69a493684ee48190bd43b7c78da4aec8 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a69dfeb08190b54a476cfa66e6d6 completed March 1, 2026, 8:50 p.m.
PD Predicate disambiguation batch_69a4a506106081909ef97a679ff00a5a completed March 1, 2026, 8:43 p.m.
Created at: March 1, 2026, 7:37 p.m.