Triple

T20973649
Position Surface form Disambiguated ID Type / Status
Subject Vovchansk region E516567 entity
Predicate contains P35 FINISHED
Object city of Vovchansk 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: city of Vovchansk | Statement: [Vovchansk region, contains, city of Vovchansk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Vovchansk
Context triple: [Vovchansk region, contains, city of Vovchansk]
  • A. Vovchansk chosen
    Vovchansk is a small city in northeastern Ukraine, located near the Russian border in Kharkiv Oblast.
  • B. Novovolynsk
    Novovolynsk is an industrial city in western Ukraine known for its coal mining history and location within Volyn Oblast near the Polish border.
  • C. Cherkassk
    Cherkassk was a historic Cossack town that served as an early administrative and cultural center in the Don region of southern Russia.
  • D. Lysychansk
    Lysychansk is an industrial city in eastern Ukraine known for its strategic location and role in the Donbas region.
  • E. Voznesensk
    Voznesensk is a city in southern Ukraine known as an industrial and transport center situated on the Southern Bug River.
  • 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_69e0b4fee5ac8190875fa9ceba1a5e5e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fba2406c8190bd75dec585c14bfa completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:45 p.m.