Triple

T19714677
Position Surface form Disambiguated ID Type / Status
Subject Naryn E473443 entity
Predicate partOf P40 FINISHED
Object Kyrgyz Republic 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: Kyrgyz Republic | Statement: [Naryn, partOf, Kyrgyz Republic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyrgyz Republic
Context triple: [Naryn, partOf, Kyrgyz Republic]
  • A. Kyrgyzstan chosen
    Kyrgyzstan is a landlocked Central Asian country known for its mountainous terrain, nomadic heritage, and status as a former Soviet republic.
  • B. Turkmenistan
    Turkmenistan is a landlocked Central Asian country rich in natural gas resources, known for its desert landscapes, authoritarian political system, and capital city Ashgabat.
  • C. Takestan
    Takestan is a city in northwestern Iran known as an important agricultural and viticultural center within Qazvin Province.
  • D. Kazakhstan
    Kazakhstan is a vast, landlocked country in Central Asia and Eastern Europe known for its rich natural resources, diverse ethnic makeup, and former status as a Soviet republic with its capital in Astana.
  • E. Saraikistan
    Saraikistan is a proposed cultural and administrative region in Pakistan envisioned as a separate province representing the Saraiki-speaking population of southern Punjab and surrounding areas.
  • 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6440b47508190a8a33325b00841dc completed April 20, 2026, 3:19 p.m.
Created at: April 10, 2026, 1:46 p.m.