Triple

T2039021
Position Surface form Disambiguated ID Type / Status
Subject Koltsevaya Line E44698 entity
Predicate hasStation P35 FINISHED
Object Taganskaya
Taganskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, known for its ornate post-war Stalinist architecture and decorative ceramic panels.
 E265589 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: Taganskaya | Statement: [Koltsevaya Line, hasStation, Taganskaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Taganskaya
Context triple: [Koltsevaya Line, hasStation, Taganskaya]
  • A. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • B. Rizhskaya
    Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
  • C. Shakhovskoye
    Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
  • D. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • E. Karamyshevskaya
    Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
  • 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: Taganskaya
Triple: [Koltsevaya Line, hasStation, Taganskaya]
Generated description
Taganskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, known for its ornate post-war Stalinist architecture and decorative ceramic panels.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Taganskaya
Target entity description: Taganskaya is a Moscow Metro station on the Koltsevaya (Circle) Line, known for its ornate post-war Stalinist architecture and decorative ceramic panels.
  • A. Voykovskaya
    Voykovskaya is a Moscow Metro station serving the Zamoskvoretskaya Line in the northern part of the city.
  • B. Rizhskaya
    Rizhskaya is a Moscow Metro station on the Big Circle Line serving the Rizhsky railway terminal area.
  • C. Shakhovskoye
    Shakhovskoye is a rural locality in Russia known primarily as the birthplace of Soviet politician Mikhail Suslov.
  • D. Paveletskaya
    Paveletskaya is a Moscow Metro station named after the nearby Paveletsky railway terminal, serving as a key transport hub in the city’s network.
  • E. Karamyshevskaya
    Karamyshevskaya is a metro station on Moscow’s Big Circle Line, serving the Khoroshyovo-Mnyovniki area of the city.
  • 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_69a889159ec481908f9e4472d9f480c7 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb951870481909dbdd8fc8b0c02fe completed March 7, 2026, 5:36 a.m.
NED1 Entity disambiguation (via context triple) batch_69aebf09d0748190bfc995031b61145f completed March 9, 2026, 12:37 p.m.
NEDg Description generation batch_69aec516cf508190ae755a3b1a8ecb73 completed March 9, 2026, 1:03 p.m.
NED2 Entity disambiguation (via description) batch_69aec592ddb48190a776c2751dbfe221 completed March 9, 2026, 1:05 p.m.
Created at: March 4, 2026, 7:39 p.m.