Triple

T3708057
Position Surface form Disambiguated ID Type / Status
Subject Azerbaijan SSR administrative divisions E80939 entity
Predicate usedLanguageInAdministration P11893 FINISHED
Object Russian 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: Russian | Statement: [Azerbaijan SSR administrative divisions, usedLanguageInAdministration, Russian]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedLanguageInAdministration
Context triple: [Azerbaijan SSR administrative divisions, usedLanguageInAdministration, Russian]
  • A. historicallyDominantLanguageOfAdministrationIn chosen
    Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
  • B. usedInLanguage
    Indicates that something (such as a word, expression, or symbol) is employed or occurs within a particular language.
  • C. governingLanguage
    Indicates the language that holds official or authoritative status over a given entity, such as a region, organization, or document.
  • D. languageOfCommunications
    Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
  • E. languageOfInterface
    Indicates the language used by or presented in a user interface.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc580b08481908391283778d5ce14 completed March 8, 2026, 6:52 p.m.
PD Predicate disambiguation batch_69adc041a8608190a2d543dab6d2ef6c completed March 8, 2026, 6:30 p.m.
Created at: March 8, 2026, 3:33 p.m.