Triple

T3985538
Position Surface form Disambiguated ID Type / Status
Subject 16th Army E86861 entity
Predicate areaOfOperations P710 FINISHED
Object Pskov region 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 region | Statement: [16th Army, areaOfOperations, Pskov region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pskov region
Context triple: [16th Army, areaOfOperations, Pskov region]
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9dfaf28819081b547836d79b889 completed March 9, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69ca392955f081909deeeae20822adc0 completed March 30, 2026, 8:49 a.m.
Created at: March 9, 2026, 3:33 p.m.