Triple

T10495879
Position Surface form Disambiguated ID Type / Status
Subject MiG-25 E247535 entity
Predicate usedBy P260 FINISHED
Object Kazakhstan E9209 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: Kazakhstan | Statement: [MiG-25, usedBy, Kazakhstan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kazakhstan
Context triple: [MiG-25, usedBy, Kazakhstan]
  • A. Kazakhstan chosen
    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.
  • B. Takestan
    Takestan is a city in northwestern Iran known as an important agricultural and viticultural center within Qazvin Province.
  • C. 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.
  • D. 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.
  • E. Kyrgyzstan
    Kyrgyzstan is a landlocked Central Asian country known for its mountainous terrain, nomadic heritage, and status as a former Soviet republic.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098be488819083d614f528cd82fb completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b1d5b388190841ed0df2145ad7a completed April 10, 2026, 9:26 p.m.
Created at: April 6, 2026, 12:24 p.m.