Triple

T17168331
Position Surface form Disambiguated ID Type / Status
Subject Rutul language E416663 entity
Predicate hasDialect P4251 FINISHED
Object Khnov dialect E1253883 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: Khnov dialect | Statement: [Rutul language, hasDialect, Khnov dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khnov dialect
Context triple: [Rutul language, hasDialect, Khnov dialect]
  • A. Borch-Khnov dialect chosen
    The Borch-Khnov dialect is a regional variety of the Rutul language spoken by Rutul communities in parts of the eastern Caucasus.
  • B. Kachinsky dialect
    The Kachinsky dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia.
  • C. Sagaysky dialect
    The Sagaysky dialect is a regional variety of the Khakas language spoken by the Sagay subgroup of the Khakas people in Siberia.
  • D. Aknogai dialect
    The Aknogai dialect is a regional variety of the Nogai language spoken by Nogai communities in the North Caucasus.
  • E. Namoluk dialect
    The Namoluk dialect is a regional variety of the Mortlockese language spoken primarily on Namoluk Atoll in the Federated States of Micronesia.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f9173ee48190bc46622c78479603 completed April 18, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fc83984819098c98b75cf021e3a completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:37 a.m.