Triple

T17948566
Position Surface form Disambiguated ID Type / Status
Subject Saint Petersburg suburban railways E448767 entity
Predicate connectsToTown P60933 FINISHED
Object Priozersk NE NERFINISHED

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: Priozersk | Statement: [Saint Petersburg suburban railways, connectsToTown, Priozersk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Priozersk
Context triple: [Saint Petersburg suburban railways, connectsToTown, Priozersk]
  • A. Priozersk chosen
    Priozersk is a small town in northwestern Russia known for its historic fortress Korela and its location on the shores of Lake Ladoga.
  • B. Votkinsk
    Votkinsk is a Russian town in Udmurtia best known as the birthplace of composer Pyotr Ilyich Tchaikovsky.
  • C. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • D. Novotroitsk
    Novotroitsk is an industrial city in Russia known for its metallurgical industry and location near the Ural Mountains.
  • E. Pervouralsk
    Pervouralsk is an industrial city in Russia’s Ural region, known for its metallurgical plants and location near the geographic border between Europe and Asia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f8cca8819099836916c56b7c95 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4afaac780819097434b20b1f155d2 completed April 19, 2026, 10:34 a.m.
Created at: April 10, 2026, 10:21 a.m.