Triple

T17325666
Position Surface form Disambiguated ID Type / Status
Subject Chuy Region E420680 entity
Predicate partOf P40 FINISHED
Object Kyrgyzstan 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: Kyrgyzstan | Statement: [Chuy Region, partOf, Kyrgyzstan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyrgyzstan
Context triple: [Chuy Region, partOf, Kyrgyzstan]
  • 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. 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.
  • C. 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.
  • D. Takestan
    Takestan is a city in northwestern Iran known as an important agricultural and viticultural center within Qazvin Province.
  • E. Tajikistan
    Tajikistan is a landlocked, mountainous country in Central Asia known for its rugged Pamir range and as a former Soviet republic with an economy centered on agriculture, hydropower, and remittances.
  • 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.