Triple

T1854168
Position Surface form Disambiguated ID Type / Status
Subject Swiss Federal Council E41663 entity
Predicate officialLanguagesUsed P30223 FINISHED
Object German 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: German | Statement: [Swiss Federal Council, officialLanguagesUsed, German]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: officialLanguagesUsed
Context triple: [Swiss Federal Council, officialLanguagesUsed, German]
  • A. officialLanguageUse chosen
    Indicates that a particular language is formally designated and used by an authority (such as a government or institution) for official communication, documentation, or functions.
  • B. officialLanguage
    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.
  • C. additionalOfficialLanguage
    Indicates that an entity has another language, beyond its primary one, that holds official or formally recognized status.
  • D. officialLanguageScope
    Indicates the scope or extent (such as region, institution, or context) within which a language holds official status.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb231de14819091da3a20ed03c430 completed March 7, 2026, 5:05 a.m.
PD Predicate disambiguation batch_69abafde4598819099d8229128348fd3 completed March 7, 2026, 4:55 a.m.
Created at: March 4, 2026, 7:33 p.m.