Triple

T38519575
Position Surface form Disambiguated ID Type / Status
Subject César Award for Best Actress – nomination for Kristin Scott Thomas E922437 entity
Predicate recognizesPerformanceLanguage P60621 FINISHED
Object French 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: French | Statement: [César Award for Best Actress – nomination for Kristin Scott Thomas, recognizesPerformanceLanguage, French]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: recognizesPerformanceLanguage
Context triple: [César Award for Best Actress – nomination for Kristin Scott Thomas, recognizesPerformanceLanguage, French]
  • A. performedLanguage
    Indicates that an action, work, or performance was carried out using a specified language.
  • B. hasTypicalPerformanceLanguage
    Indicates that an entity is commonly or characteristically expressed, implemented, or described using a particular programming or specification language.
  • C. recognizedLanguage
    Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
  • D. recognisesLanguageAs
    Indicates that one entity acknowledges or accepts a particular language as valid, appropriate, or officially recognized in a given context.
  • E. repertoireLanguage chosen
    Indicates that the associated entity’s repertoire (e.g., works, performances, or outputs) is expressed or available in a particular language.
  • 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_69f76ea5f5588190bd0b28c82e975640 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fe0d165a48819098b854318a50d76c completed May 8, 2026, 4:19 p.m.
PD Predicate disambiguation batch_69fe0931002481908a95b34f95e9f64e completed May 8, 2026, 4:02 p.m.
Created at: May 3, 2026, 4:32 p.m.