Triple

T1231495
Position Surface form Disambiguated ID Type / Status
Subject Grozny E26451 entity
Predicate officialLanguage P236 FINISHED
Object Chechen E90390 NE 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: Chechen | Statement: [Grozny, officialLanguage, Chechen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chechen
Context triple: [Grozny, officialLanguage, Chechen]
  • A. Chechen language chosen
    The Chechen language is a Northeast Caucasian language primarily spoken in the Chechen Republic of Russia and by Chechen communities in the Caucasus and diaspora.
  • B. Chechens
    Chechens are a predominantly Muslim ethnic group native to the North Caucasus region, known for their distinct language, culture, and strong clan-based social traditions.
  • C. Chuvash
    Chuvash are a Turkic ethnic group native to the Volga region of Russia, known for their distinct Chuvash language and culture.
  • D. Abkhaz–Abaza
    Abkhaz–Abaza is a small Northwest Caucasian language subgroup comprising closely related languages spoken primarily in Abkhazia and parts of the North Caucasus.
  • E. Chechnya
    Chechnya is a predominantly Muslim republic in the North Caucasus region of Russia, known for its mountainous terrain, complex ethnic history, and conflicts with the Russian state.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69a4948571c88190a9191e451e6035fd completed March 1, 2026, 7:33 p.m.
NER Named-entity recognition batch_69a4be5a25348190a0665b6324c4d8f5 completed March 1, 2026, 10:31 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac8a1457a08190aef2f7fed6c6725f completed March 7, 2026, 8:27 p.m.
Created at: March 1, 2026, 7:47 p.m.