Triple

T9935491
Position Surface form Disambiguated ID Type / Status
Subject Wilmès II Government E192748 entity
Predicate languageCommunityContext P5562 FINISHED
Object bilingual French–Dutch federal government 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: bilingual French–Dutch federal government | Statement: [Wilmès II Government, languageCommunityContext, bilingual French–Dutch federal government]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageCommunityContext
Context triple: [Wilmès II Government, languageCommunityContext, bilingual French–Dutch federal government]
  • A. languageLocalCommunities
    Indicates that a language is used, maintained, or holds significance within specific local communities or regions.
  • B. hasLanguageCommunity chosen
    Indicates that an entity is associated with or serves a particular language community.
  • C. ethnicCommunityBase
    Indicates that an ethnic community is based in, originates from, or is primarily associated with a particular place or area.
  • D. languageDiversity
    Indicates the degree to which multiple distinct languages are present and used within a given context or population.
  • E. languageFamilyContext
    Indicates the broader linguistic family or grouping within which a particular language or linguistic element is situated.
  • 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_69ca82dd978c8190947124ab0d3315ac completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5e3bfa88190a88f20f2687a2583 completed April 2, 2026, 12:18 a.m.
PD Predicate disambiguation batch_69cd1d9428cc81909b4b4938566d78a7 completed April 1, 2026, 1:28 p.m.
Created at: March 30, 2026, 8:44 p.m.