Triple

T12475076
Position Surface form Disambiguated ID Type / Status
Subject RU-CFD E298154 entity
Predicate includesRegion P285 FINISHED
Object Orel Oblast 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: Orel Oblast | Statement: [RU-CFD, includesRegion, Orel Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orel Oblast
Context triple: [RU-CFD, includesRegion, Orel Oblast]
  • A. Oryol Oblast chosen
    Oryol Oblast is a federal subject of western Russia known for its historic role as a major World War II battleground and its agricultural and industrial economy centered around the city of Oryol.
  • B. Kaluga Oblast
    Kaluga Oblast is a federal subject of western Russia known for its historical cities, space industry heritage, and location southwest of Moscow.
  • C. Penza Oblast
    Penza Oblast is a federal subject of central Russia known for its agricultural economy, mixed forests, and role as a regional industrial and cultural center.
  • D. Kostroma Oblast
    Kostroma Oblast is a federal subject in central Russia known for its historic towns and forests, situated along the middle reaches of the Volga River.
  • E. Smolensk Oblast
    Smolensk Oblast is a federal subject of western Russia known for its historic city of Smolensk and its location along the route between Moscow and Belarus.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcb194c81908b5e0320ddfd463c completed April 10, 2026, 7:21 p.m.
Created at: April 8, 2026, 9:56 p.m.