Triple

T64042
Position Surface form Disambiguated ID Type / Status
Subject General Secretary of the Communist Party of the Soviet Union E1272 entity
Predicate nativeNameLanguage P15 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: [General Secretary of the Communist Party of the Soviet Union, nativeNameLanguage, Russian]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: nativeNameLanguage
Context triple: [General Secretary of the Communist Party of the Soviet Union, nativeNameLanguage, Russian]
  • A. nativeLanguage
    Indicates the language that a person or entity originally learned and uses as their primary or first language.
  • B. primaryLanguageOf
    Indicates that a specified language is the main or official language used by a particular entity (such as a person, organization, or region).
  • C. languageOfWorkOrName chosen
    Indicates the language in which a work is created or a name is expressed.
  • D. hasEndonym
    Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
  • E. 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.
  • 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_69a24ba4f760819081f6638a3c70538a completed Feb. 28, 2026, 1:57 a.m.
NER Named-entity recognition batch_69a24fd16c248190a6ee4cd96c388772 completed Feb. 28, 2026, 2:15 a.m.
PD Predicate disambiguation batch_69a24ea3c44081908fa3856969881d1f completed Feb. 28, 2026, 2:10 a.m.
Created at: Feb. 28, 2026, 2:02 a.m.