Triple

T17325816
Position Surface form Disambiguated ID Type / Status
Subject Karakol ski base E420684 entity
Predicate locatedIn P40 FINISHED
Object Karakol 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: Karakol | Statement: [Karakol ski base, locatedIn, Karakol]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karakol
Context triple: [Karakol ski base, locatedIn, Karakol]
  • A. Karakol chosen
    Karakol is a town in eastern Kyrgyzstan near Lake Issyk-Kul, known as a gateway to the Tien Shan Mountains and a center for trekking and skiing.
  • B. Bazar-Korgon
    Bazar-Korgon is a town in southwestern Kyrgyzstan, known as a local administrative and market center in the Jalal-Abad Region.
  • C. Kochkor-Ata
    Kochkor-Ata is a town in western Kyrgyzstan known for its role in regional industry and its location near key transport and energy infrastructure.
  • D. Khinalug
    Khinalug is one of the oldest continuously inhabited mountain villages in the Caucasus, known for its unique language and remote location in the highlands of northern Azerbaijan.
  • E. Dastakert
    Dastakert is a small town in southern Armenia known for its mountainous setting and former mining industry.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d24e548190a766dd246a4d63d4 completed April 19, 2026, 2:11 a.m.
Created at: April 10, 2026, 5:43 a.m.