Triple

T9650879
Position Surface form Disambiguated ID Type / Status
Subject South Kazakhstan Region E233329 entity
Predicate capital P234 FINISHED
Object Shymkent E51721 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: Shymkent | Statement: [South Kazakhstan Region, capital, Shymkent]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shymkent
Context triple: [South Kazakhstan Region, capital, Shymkent]
  • A. Shymkent chosen
    Shymkent is one of the largest and most populous cities in southern Kazakhstan, serving as a key industrial, commercial, and cultural center of the region.
  • B. Almaty
    Almaty is the largest city and main commercial and cultural center of Kazakhstan, located in the country’s mountainous southeast.
  • C. Karaganda
    Karaganda is a large industrial city in central Kazakhstan known for its coal mining industry and Soviet-era history.
  • D. Kyzylorda
    Kyzylorda is a city in south-central Kazakhstan known as an important regional center on the Syr Darya River with historical ties to the early development of the Kazakh Soviet Republic.
  • E. Pavlodar
    Pavlodar is a major industrial and cultural city in northeastern Kazakhstan, located on the Irtysh River.
  • 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_69ca848b31648190b57aa55da20285be completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9baf9a1c819098c407ea7d42e6d1 completed April 1, 2026, 10:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1826780fc81909c418e82bd94c581 completed April 4, 2026, 9:28 p.m.
Created at: March 30, 2026, 8:13 p.m.