Triple

T12658216
Position Surface form Disambiguated ID Type / Status
Subject Negidal language E302343 entity
Predicate languageShiftCause P23674 FINISHED
Object Russification policies 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: Russification policies | Statement: [Negidal language, languageShiftCause, Russification policies]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: languageShiftCause
Context triple: [Negidal language, languageShiftCause, Russification policies]
  • A. languageShift
    Indicates a change in the primary language used by an entity, such as switching from one language to another over time or in a given context.
  • B. languageAffected
    Indicates that one entity has an impact on, modifies, or influences the characteristics, usage, or status of a language.
  • C. causeOfLanguageShift chosen
    Indicates a factor or event that leads to a change from one dominant language or linguistic pattern to another within a community or population.
  • D. languageShiftPressureFrom
    Indicates pressure exerted by one entity that causes or encourages another entity to shift away from its current language toward a different language.
  • E. riskOfLanguageShift
    Indicates that there is a likelihood or tendency for one language to be replaced or significantly reduced in use by another within a given community or context.
  • 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_69d7bded71a88190bb76e2413af9ea66 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d9617b07ec8190b714f04ae6654060 completed April 10, 2026, 8:45 p.m.
PD Predicate disambiguation batch_69d960b78ce8819091f15dd5013e6da5 completed April 10, 2026, 8:42 p.m.
Created at: April 9, 2026, 5:19 p.m.