Triple

T14406623
Position Surface form Disambiguated ID Type / Status
Subject Nikopol E357212 entity
Predicate locatedSouthOf P9676 FINISHED
Object Dnipro (city) E38828 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: Dnipro (city) | Statement: [Nikopol, locatedSouthOf, Dnipro (city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dnipro (city)
Context triple: [Nikopol, locatedSouthOf, Dnipro (city)]
  • 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. 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. 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 (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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de908804048190a4fe58afc2e0a5b6 completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5be63848190aa71f009ceaea1b3 completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:17 a.m.