Triple

T16026084
Position Surface form Disambiguated ID Type / Status
Subject Qipchaq Uzbek E388720 entity
Predicate sharesFeaturesWith P5696 FINISHED
Object Kyrgyz language E72799 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: Kyrgyz language | Statement: [Qipchaq Uzbek, sharesFeaturesWith, Kyrgyz language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyrgyz language
Context triple: [Qipchaq Uzbek, sharesFeaturesWith, Kyrgyz language]
  • A. Kyrgyz chosen
    Kyrgyz is a Turkic language primarily spoken in Kyrgyzstan and surrounding regions of Central Asia.
  • B. Turkmen language
    The Turkmen language is a Turkic language spoken primarily in Turkmenistan and surrounding regions, closely related to Turkish and other Oghuz languages.
  • C. Kazakh language
    The Kazakh language is a Turkic language spoken primarily in Kazakhstan and surrounding regions, written today mainly in Cyrillic but also in Latin and Arabic scripts.
  • D. Khinalug language
    The Khinalug language is a highly endangered Northeast Caucasian language spoken by the Khinalug people in a single mountain village in northern Azerbaijan.
  • E. Saryk dialect
    The Saryk dialect is a regional variety of the Turkmen language traditionally spoken by the Saryk Turkmen people of Central Asia.
  • 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1832790548190a74045d554e13328 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf31c8d8819096c562ba1453f3c0 completed May 10, 2026, 12:20 a.m.
Created at: April 10, 2026, 4:56 a.m.