Triple

T3891201
Position Surface form Disambiguated ID Type / Status
Subject Northwest Russia E88065 entity
Predicate includes P1393 FINISHED
Object Pskov Oblast E82903 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: Pskov Oblast | Statement: [Northwest Russia, includes, Pskov Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pskov Oblast
Context triple: [Northwest Russia, includes, Pskov Oblast]
  • A. Pskov Oblast chosen
    Pskov Oblast is a federal subject of western Russia bordering the Baltic states and Belarus, known for its historic city of Pskov and numerous medieval fortresses.
  • B. Novgorod Oblast
    Novgorod Oblast is a federal subject of Russia known for its historic cities, including Veliky Novgorod, one of the oldest and most culturally significant centers in the country.
  • C. 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.
  • 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. 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_69aed9466d548190939f5217a23ed4ac completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeecb0ba448190aa076865b7762002 completed March 9, 2026, 3:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca1463cacc8190b143ab1ced648ec7 completed March 30, 2026, 6:12 a.m.
Created at: March 9, 2026, 3:21 p.m.