Triple

T1946728
Position Surface form Disambiguated ID Type / Status
Subject Sokolnicheskaya Line E42070 entity
Predicate hasStation P35 FINISHED
Object Sokolniki station
Sokolniki station is a Moscow Metro station on one of the system’s oldest and most central lines, serving the Sokolniki district.
 E302422 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: Sokolniki station | Statement: [Sokolnicheskaya Line, hasStation, Sokolniki station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sokolniki station
Context triple: [Sokolnicheskaya Line, hasStation, Sokolniki station]
  • A. Dzerzhinskaya station
    Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Bulvar Rokossovskogo station
    Bulvar Rokossovskogo station is a Moscow Metro station serving as the northeastern terminus of the Sokolnicheskaya Line.
  • D. Ploshchad Truda station
    Ploshchad Truda station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • E. Komsomolskaya station
    Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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: Sokolniki station
Triple: [Sokolnicheskaya Line, hasStation, Sokolniki station]
Generated description
Sokolniki station is a Moscow Metro station on one of the system’s oldest and most central lines, serving the Sokolniki district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sokolniki station
Target entity description: Sokolniki station is a Moscow Metro station on one of the system’s oldest and most central lines, serving the Sokolniki district.
  • A. Dzerzhinskaya station
    Dzerzhinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Kachinskaya station
    Kachinskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Bulvar Rokossovskogo station
    Bulvar Rokossovskogo station is a Moscow Metro station serving as the northeastern terminus of the Sokolnicheskaya Line.
  • D. Ploshchad Truda station
    Ploshchad Truda station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • E. Komsomolskaya station
    Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69afce7154648190aa55d54ca5e50559 completed March 10, 2026, 7:55 a.m.
NEDg Description generation batch_69afd22a81dc8190809f94f8e49ddad8 completed March 10, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_69afd3b8daec81908c5d507e35ba997e completed March 10, 2026, 8:18 a.m.
Created at: March 4, 2026, 7:36 p.m.