Triple

T17480897
Position Surface form Disambiguated ID Type / Status
Subject Savyolovsky railway terminal E425654 entity
Predicate connectsTo P845 FINISHED
Object Khimki 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: Khimki | Statement: [Savyolovsky railway terminal, connectsTo, Khimki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Khimki
Context triple: [Savyolovsky railway terminal, connectsTo, Khimki]
  • A. Khimki chosen
    Khimki is a city in Moscow Oblast, Russia, forming part of the Moscow metropolitan area and known for its proximity to major transport hubs and industrial facilities.
  • B. Pirogovo
    Pirogovo is a settlement located near the Pirogovskoye Reservoir, known as a local residential and recreational area.
  • C. Sokolka
    Sokolka is a town in present-day northeastern Poland, historically part of the Grodno region, known for its multicultural heritage and role as a local administrative and trade center.
  • D. Krylatskoye
    Krylatskoye is a Moscow Metro station serving the Krylatskoye District in western Moscow, Russia.
  • E. Kireyevsk
    Kireyevsk is a small industrial town in western Russia known for its coal-mining history and location within the Tula region.
  • 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_69d889dccf7481909264a1844a2e9100 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451bfd75481908c20bc2c1cbff593 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:48 a.m.