Triple

T10640323
Position Surface form Disambiguated ID Type / Status
Subject D4 E250702 entity
Predicate regionServed P82 FINISHED
Object Moscow region 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 region | Statement: [D4, regionServed, Moscow region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Moscow region
Context triple: [D4, regionServed, Moscow region]
  • 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. Moscow Governorate
    Moscow Governorate was a major administrative division of the Russian Empire centered around Moscow, serving as a key political, economic, and cultural region.
  • C. 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.
  • D. 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.
  • E. Belgorod region
    The Belgorod region is an area in western Russia near the Ukrainian border, historically notable as a major World War II battleground and now an important agricultural and industrial region.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfcbe5308190986bba438d19e852 completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69dff76eef4c8190b4fe681a9431207d completed April 15, 2026, 8:39 p.m.
Created at: April 8, 2026, 9:04 p.m.