Triple

T9099975
Position Surface form Disambiguated ID Type / Status
Subject Nogai E218126 entity
Predicate hasDialect P4251 FINISHED
Object Aknogai dialect E670721 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: Aknogai dialect | Statement: [Nogai, hasDialect, Aknogai dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aknogai dialect
Context triple: [Nogai, hasDialect, Aknogai dialect]
  • A. Aknogai dialect chosen
    The Aknogai dialect is a regional variety of the Nogai language spoken by Nogai communities in the North Caucasus.
  • B. Karanogai dialect
    The Karanogai dialect is a regional variety of the Nogai Turkic language spoken by Nogai communities, distinguished by its own phonetic and lexical features.
  • C. Akusha dialect
    The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
  • D. Noatia dialect
    The Noatia dialect is a regional variety of the Kokborok language spoken primarily by the Noatia community in Tripura, India.
  • E. Nohurli dialect
    The Nohurli dialect is a regional variety of Turkmen spoken by the Nohur people in parts of Turkmenistan, distinguished by its unique phonetic and lexical features.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc9710ac04819096b9c8d3399b9c35 completed April 1, 2026, 3:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69d030201a048190a3a1166d23c5ae67 completed April 3, 2026, 9:24 p.m.
Created at: March 30, 2026, 7:15 p.m.