Triple

T20462052
Position Surface form Disambiguated ID Type / Status
Subject Buynaksk dialect E501947 entity
Predicate associatedWith P37 FINISHED
Object Buynaksky District NE NERFINISHED

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: Buynaksky District | Statement: [Buynaksk dialect, associatedWith, Buynaksky District]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buynaksky District
Context triple: [Buynaksk dialect, associatedWith, Buynaksky District]
  • A. Buynaksky District chosen
    Buynaksky District is an administrative district (raion) in the Republic of Dagestan, Russia, with its administrative center in the town of Buynaksk.
  • B. Nukus District
    Nukus District is an administrative district centered around the city of Nukus in the autonomous Republic of Karakalpakstan in northwestern Uzbekistan.
  • C. Gazakh District
    Gazakh District is an administrative region in western Azerbaijan known for its strategic location near the borders with Georgia and Armenia and its role as a historical and cultural center.
  • D. Kazygurt District
    Kazygurt District is an administrative district in southern Kazakhstan known for its rural communities and the prominent Kazygurt mountain range.
  • E. Nurgal District
    Nurgal District is an administrative district located in Kunar Province in eastern Afghanistan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a761648190b24cf4bb90a8abb1 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.