Triple

T9101298
Position Surface form Disambiguated ID Type / Status
Subject Горки E218161 entity
Predicate locatedIn P40 FINISHED
Object Московская область 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: Московская область | Statement: [Горки, locatedIn, Московская область]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Московская область
Context triple: [Горки, locatedIn, Московская область]
  • 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. 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.
  • C. 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.
  • 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. Yaroslavl Oblast
    Yaroslavl Oblast is a federal subject of central Russia known for its historic cities along the Volga River and its role as part of the country’s Golden Ring tourist route.
  • 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_69ca83d9844081908e561e367fda6d45 completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69cc971435d08190b5007ed44ac0a364 completed April 1, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0182d8ea08190b4337a77b47019a5 completed April 3, 2026, 7:42 p.m.
Created at: March 30, 2026, 7:15 p.m.