Triple

T18754395
Position Surface form Disambiguated ID Type / Status
Subject Nur Alem museum of future energy E458610 entity
Predicate locatedIn P40 FINISHED
Object Akmola Region 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: Akmola Region | Statement: [Nur Alem museum of future energy, locatedIn, Akmola Region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akmola Region
Context triple: [Nur Alem museum of future energy, locatedIn, Akmola Region]
  • A. Akmola Region chosen
    Akmola Region is a central administrative region of Kazakhstan that includes the nation’s capital, Astana, and serves as an important political and economic hub.
  • B. Akmola
    Akmola is the former name of Kazakhstan’s capital city, now known as Astana.
  • C. Kostanay Region
    Kostanay Region is a large administrative region in northern Kazakhstan known for its agricultural production and proximity to the Russian border.
  • D. Kyzylorda Region
    Kyzylorda Region is an administrative region in southern Kazakhstan known for hosting the Baikonur Cosmodrome, the world’s first and largest operational space launch facility.
  • E. North Kazakhstan Region
    North Kazakhstan Region is an administrative region in northern Kazakhstan known for its agricultural economy, steppe landscapes, and proximity to the Russian border.
  • 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e579ef4ee48190a9892ac9787ffe37 completed April 20, 2026, 12:57 a.m.
Created at: April 10, 2026, 11:51 a.m.