Triple

T30864684
Position Surface form Disambiguated ID Type / Status
Subject Les Eurockéennes de Belfort E786163 entity
Predicate languageOfAudienceInformation P94660 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: [Les Eurockéennes de Belfort, languageOfAudienceInformation, French]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageOfAudienceInformation
Context triple: [Les Eurockéennes de Belfort, languageOfAudienceInformation, French]
  • A. hasTargetAudienceLanguage chosen
    Indicates that something is intended for or directed toward an audience that speaks a particular language.
  • B. languageOfSurroundingCulture
    Indicates that one entity is the language predominantly used or characteristic of the surrounding culture associated with another entity.
  • C. languageOfSources
    Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
  • D. languageSpokenOnScreen
    Indicates that a particular language is used in spoken dialogue or audible communication within an on-screen work (such as a film, show, or video).
  • E. languageOfCoverage
    Indicates the language in which the coverage, such as reporting or documentation about something, is expressed.
  • 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_69f224b9df2c819086f55f8bcf7f382e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69ff3fb2318c81908a46c2f513608935 completed May 9, 2026, 2:07 p.m.
PD Predicate disambiguation batch_69ff3e96dcc48190819f6204680d84aa completed May 9, 2026, 2:03 p.m.
Created at: April 29, 2026, 8:47 p.m.