Triple

T10059525
Position Surface form Disambiguated ID Type / Status
Subject Giảng Võ Ward E208946 entity
Predicate hasLanguageUsedForAdministration P86356 FINISHED
Object Vietnamese 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: Vietnamese | Statement: [Giảng Võ Ward, hasLanguageUsedForAdministration, Vietnamese]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLanguageUsedForAdministration
Context triple: [Giảng Võ Ward, hasLanguageUsedForAdministration, Vietnamese]
  • A. usesLanguageForAdministration chosen
    Indicates that an entity employs a particular language as the official medium for its administrative or governmental functions.
  • B. historicallyDominantLanguageOfAdministrationIn
    Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
  • C. hasLanguageStatus
    Indicates that an entity has a particular status or condition regarding its language use, recognition, or classification.
  • D. languageOfAwardAdministration
    Indicates the language used to administer, manage, or conduct the award process.
  • E. laterSecondaryLanguageOfAdministration
    Indicates that one language served as a subsequent or later secondary language used for administrative purposes in relation to another language.
  • 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_69ca836094408190a36a1ea7e9a86fcd completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcfd0d23081909510785ef8a186a3 completed April 2, 2026, 2:09 a.m.
PD Predicate disambiguation batch_69cd4b92573481909389bc6148ae7ea8 completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 8:57 p.m.