Triple

T13129759
Position Surface form Disambiguated ID Type / Status
Subject Vyborgsky District E311936 entity
Predicate hasMetroStation P522 FINISHED
Object Lesnaya
Lesnaya is a metro station in Saint Petersburg, Russia, serving the Vyborgsky District on the city's rapid transit network.
E1044270 NE FINISHED

How this triple was built (4 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: Lesnaya | Statement: [Vyborgsky District, hasMetroStation, Lesnaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lesnaya
Context triple: [Vyborgsky District, hasMetroStation, Lesnaya]
  • A. Lesnaya
    Lesnaya is a village in present-day Belarus historically notable as the site of the 1708 Battle of Lesnaya during the Great Northern War.
  • B. Lesnoy Gorodok
    Lesnoy Gorodok is a suburban settlement in the Moscow region of Russia, known primarily as a residential community within the greater Moscow metropolitan area.
  • C. Lesnoy
    Lesnoy is a closed town in Russia’s Sverdlovsk Oblast known for its role in the country’s nuclear and defense industries.
  • D. Lesnoy
    Lesnoy is a rural settlement located within the Vyborgsky District of Leningrad Oblast in northwestern Russia.
  • E. Yartsevo
    Yartsevo is a town in western Russia known as an industrial center within Smolensk Oblast.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lesnaya
Triple: [Vyborgsky District, hasMetroStation, Lesnaya]
Generated description
Lesnaya is a metro station in Saint Petersburg, Russia, serving the Vyborgsky District on the city's rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lesnaya
Target entity description: Lesnaya is a metro station in Saint Petersburg, Russia, serving the Vyborgsky District on the city's rapid transit network.
  • A. Lesnaya
    Lesnaya is a village in present-day Belarus historically notable as the site of the 1708 Battle of Lesnaya during the Great Northern War.
  • B. Lesnoy Gorodok
    Lesnoy Gorodok is a suburban settlement in the Moscow region of Russia, known primarily as a residential community within the greater Moscow metropolitan area.
  • C. Lesnoy
    Lesnoy is a closed town in Russia’s Sverdlovsk Oblast known for its role in the country’s nuclear and defense industries.
  • D. Lesnoy
    Lesnoy is a rural settlement located within the Vyborgsky District of Leningrad Oblast in northwestern Russia.
  • E. Yartsevo
    Yartsevo is a town in western Russia known as an industrial center within Smolensk Oblast.
  • F. None of above. chosen

Provenance (5 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9819bfd348190a22d44f837877e1c completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7546b9ae081909f97fc4a06b8f927 completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f756902b0481909085473ab48c39db completed May 3, 2026, 2:07 p.m.
NED2 Entity disambiguation (via description) batch_69f756ebe5788190acc56b8c92a4bf0a completed May 3, 2026, 2:08 p.m.
Created at: April 9, 2026, 9:07 p.m.