Triple

T12475068
Position Surface form Disambiguated ID Type / Status
Subject RU-CFD E298154 entity
Predicate includesRegion P285 FINISHED
Object Moscow Oblast E13313 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: Moscow Oblast | Statement: [RU-CFD, includesRegion, Moscow Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow Oblast
Context triple: [RU-CFD, includesRegion, Moscow Oblast]
  • A. Moscow Oblast chosen
    Moscow Oblast is a federal subject of Russia that surrounds, but does not include, the city of Moscow and serves as a major industrial and population center in western Russia.
  • B. Ryazan Oblast
    Ryazan Oblast is a federal subject of central Russia known for its historic cities, agricultural landscapes, and location along the Oka River southeast of Moscow.
  • C. Nizhny Novgorod Oblast
    Nizhny Novgorod Oblast is a federal subject of central Russia known for its major industrial centers, historical cities, and strategic location along the Volga River.
  • D. Kaluga Oblast
    Kaluga Oblast is a federal subject of western Russia known for its historical cities, space industry heritage, and location southwest of Moscow.
  • E. Tver Oblast
    Tver Oblast is a federal subject of western Russia known for its forests, lakes, and historic towns, and for encompassing the headwaters of major rivers including the Volga.
  • 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_69d6ada270808190b1a2b2e7b02bb426 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94dcb194c81908b5e0320ddfd463c completed April 10, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68e99c2608190b923ca8a9178fea2 completed May 2, 2026, 11:54 p.m.
Created at: April 8, 2026, 9:56 p.m.