Triple

T22754669
Position Surface form Disambiguated ID Type / Status
Subject Kremenchuk Uyezd E562805 entity
Predicate capital P234 FINISHED
Object Kremenchuk 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: Kremenchuk | Statement: [Kremenchuk Uyezd, capital, Kremenchuk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kremenchuk
Context triple: [Kremenchuk Uyezd, capital, Kremenchuk]
  • A. Kremenchuk chosen
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • B. Kirovograd
    Kirovograd is a city in central Ukraine, historically significant as a strategic site during World War II and now known as Kropyvnytskyi.
  • C. Dniprodzerzhynsk
    Dniprodzerzhynsk (now officially called Kamianske) is an industrial city in central Ukraine known for its heavy industry and metallurgical enterprises along the Dnieper River.
  • D. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • E. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f179bc48788190b3deb9287d02cb2c completed April 29, 2026, 3:23 a.m.
Created at: April 17, 2026, 3:25 p.m.