Triple

T763202
Position Surface form Disambiguated ID Type / Status
Subject Grand maître de la Légion d'honneur E16115 entity
Predicate langueOfficielle P236 FINISHED
Object français 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: français | Statement: [Grand maître de la Légion d'honneur, langueOfficielle, français]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: langueOfficielle
Context triple: [Grand maître de la Légion d'honneur, langueOfficielle, français]
  • A. officialLanguage chosen
    Indicates that a particular language has been formally designated by an authority as the official language used for government, legal, or administrative purposes in a given jurisdiction.
  • B. additionalOfficialLanguage
    Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
  • C. languageOfOfficialAnnouncements
    Indicates the language used for formal or official public announcements issued by an authority.
  • D. standardLanguageOf
    Indicates that one entity serves as the officially recognized or commonly used standard language for another entity (such as a country, region, or organization).
  • E. oneOfSixOfficialLanguagesOf
    Indicates that a language is one of the six officially recognized languages of a particular organization, institution, or entity.
  • 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_69a4a69c8c448190a036a04fd8fdd2c2 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.