Triple

T10083183
Position Surface form Disambiguated ID Type / Status
Subject Vorskla River E213951 entity
Predicate passesNear P416 FINISHED
Object Kremenchuk E247270 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: Kremenchuk | Statement: [Vorskla River, passesNear, Kremenchuk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kremenchuk
Context triple: [Vorskla River, passesNear, 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. 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.
  • C. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • D. Kharkiv
    Kharkiv is Ukraine’s second-largest city and a major industrial, cultural, and educational center in the northeast of the country.
  • E. Khmilnyk
    Khmilnyk is a spa and resort town in central Ukraine known for its radon mineral waters and therapeutic health facilities.
  • 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_69ca839bf730819086900c323c9b8c95 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd04352d081908f676444cd2d2578 completed April 2, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d95e437d4481908a722a6648b62b39 completed April 10, 2026, 8:32 p.m.
Created at: March 30, 2026, 9 p.m.