Triple

T21240705
Position Surface form Disambiguated ID Type / Status
Subject Severodonetsk E523460 entity
Predicate alternativeName P39 FINISHED
Object Sievierodonetsk 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: Sievierodonetsk | Statement: [Severodonetsk, alternativeName, Sievierodonetsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sievierodonetsk
Context triple: [Severodonetsk, alternativeName, Sievierodonetsk]
  • A. Sievierodonetsk chosen
    Sievierodonetsk is an industrial city in eastern Ukraine that became a focal point of intense fighting during the war in the Donbas and the 2022 Russian invasion.
  • B. Kakhovskaya
    Kakhovskaya is a Moscow Metro station that serves as part of the city’s Big Circle Line.
  • C. Chornomorske
    Chornomorske is a coastal settlement in western Crimea known for its location on the Black Sea and its role as a local resort and fishing community.
  • D. Kryvyi Rih
    Kryvyi Rih is a major industrial city in central Ukraine known for its extensive iron ore mining and steel production.
  • E. Shepetivka
    Shepetivka is a city in western Ukraine known as the birthplace of prominent Russian politician Valentina Matviyenko.
  • 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_69e0b513b89c81908b27147e91368db2 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e735239f48819091ffe518b1aed2e8 completed April 21, 2026, 8:28 a.m.
Created at: April 16, 2026, 3:47 p.m.