Triple

T33911196
Position Surface form Disambiguated ID Type / Status
Subject Zorg E869317 entity
Predicate filmLanguageContext P103547 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: [Zorg, filmLanguageContext, French]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: filmLanguageContext
Context triple: [Zorg, filmLanguageContext, French]
  • A. filmLanguageFormat
    Indicates the specific language and presentation format (e.g., dubbed, subtitled, original audio) in which a film is released or available.
  • B. basedInFilmLanguage
    Indicates that something is created, presented, or expressed using the language employed in a particular film.
  • C. filmedInLanguage chosen
    Indicates that a film or video work was originally recorded using a particular spoken or signed language.
  • D. basedOnFilmLanguage
    Indicates that something is derived from, adapted from, or otherwise grounded in the language used in a particular film.
  • E. areSpokenIn
    Indicates that a particular language is used as a spoken means of communication within a specified region, community, or context.
  • 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_69f3499869bc8190b6c33a81686af226 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7051ad6e4819095e82bbd64761803 completed May 3, 2026, 8:19 a.m.
PD Predicate disambiguation batch_69f700fe24e08190998e2c96fbaaad38 completed May 3, 2026, 8:02 a.m.
Created at: May 1, 2026, 1:48 a.m.