Triple

T5216841
Position Surface form Disambiguated ID Type / Status
Subject Pskov E117772 entity
Predicate countrySubdivision P766 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: [Pskov, countrySubdivision, Pskov Oblast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pskov Oblast
Context triple: [Pskov, countrySubdivision, 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_69bd4464ba3c8190bc16b2ebbe42ddb0 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7a95abdc8190b0babd79cea1360e completed March 20, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69d5087b394c8190baa1ef5dbc92a0c8 completed April 7, 2026, 1:36 p.m.
Created at: March 20, 2026, 1:48 p.m.