Triple

T8815514
Position Surface form Disambiguated ID Type / Status
Subject Donetsk Oblast E209766 entity
Predicate borderWith P224 FINISHED
Object Luhansk Oblast E213097 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: Luhansk Oblast | Statement: [Donetsk Oblast, borderWith, Luhansk Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luhansk Oblast
Context triple: [Donetsk Oblast, borderWith, Luhansk Oblast]
  • A. Luhansk Oblast chosen
    Luhansk Oblast is an eastern Ukrainian region that forms part of the industrial Donbas area and has been a focal point of the Russo-Ukrainian conflict.
  • B. Donetsk Oblast
    Donetsk Oblast is an industrial and heavily urbanized region in eastern Ukraine, historically known for coal mining and metallurgy and currently a focal point of the Russo-Ukrainian conflict.
  • C. Zaporizhzhia Oblast
    Zaporizhzhia Oblast is a southeastern region of Ukraine that has become a major frontline area and strategic hotspot during the ongoing conflict with Russia.
  • D. Kharkiv Oblast
    Kharkiv Oblast is a northeastern region of Ukraine that has become a major frontline area and focal point of fighting during the Russo-Ukrainian War.
  • E. Mykolaiv Oblast
    Mykolaiv Oblast is an administrative region in southern Ukraine known for its Black Sea coastline, shipbuilding industry, and strategic maritime location.
  • 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_69ca8363f3308190a47e3f1ebd51f613 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ff2ff248190bafcafe8b3860e53 completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69d0f3391ff08190a725b0549fb0bc89 completed April 4, 2026, 11:17 a.m.
Created at: March 30, 2026, 6:45 p.m.