Triple

T17709775
Position Surface form Disambiguated ID Type / Status
Subject Sviatoshynsko–Brovarska line E441531 entity
Predicate hasInterchangeStation P2413 FINISHED
Object Dnipro 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: Dnipro | Statement: [Sviatoshynsko–Brovarska line, hasInterchangeStation, Dnipro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dnipro
Context triple: [Sviatoshynsko–Brovarska line, hasInterchangeStation, Dnipro]
  • A. Dnipro chosen
    Dnipro is one of Ukraine’s largest industrial and cultural centers, located on the Dnieper River in the central-eastern part of the country.
  • B. Oleksandriia
    Oleksandriia is a city in central Ukraine known as an industrial and transport hub within the Kirovohrad region.
  • C. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • D. Kremenchuk
    Kremenchuk is an industrial city in central Ukraine on the Dnieper River, historically significant as a major transport and strategic hub.
  • 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_69d8b9ea20b48190ace88bb46b01e6a9 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4729a9a9c81908d65ff0bda12c961 completed April 19, 2026, 6:13 a.m.
Created at: April 10, 2026, 10:05 a.m.