Triple

T7910328
Position Surface form Disambiguated ID Type / Status
Subject Vladimirskaya metro station E183679 entity
Predicate nativeName P15 FINISHED
Object Владимирская
Владимирская is a station of the Saint Petersburg Metro in Russia, serving the city’s central area.
 E700787 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: Владимирская | Statement: [Vladimirskaya metro station, nativeName, Владимирская]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Владимирская
Context triple: [Vladimirskaya metro station, nativeName, Владимирская]
  • A. Volzhsky
    Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
  • B. Zarechny
    Zarechny is a small Russian city in Sverdlovsk Oblast known for its role in the region’s industrial and energy sectors.
  • C. Tulskaya
    Tulskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Tulskaya Square area in southern Moscow.
  • D. Verkhnyaya Troitsa
    Verkhnyaya Troitsa is a rural locality in Russia best known as the birthplace of Soviet statesman and longtime nominal head of state Mikhail Kalinin.
  • E. Nizhegorodskaya
    Nizhegorodskaya is a Moscow Metro station on the Big Circle Line serving the Nizhegorodsky District in the southeast 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: Владимирская
Triple: [Vladimirskaya metro station, nativeName, Владимирская]
Generated description
Владимирская is a station of the Saint Petersburg Metro in Russia, serving the city’s central area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Владимирская
Target entity description: Владимирская is a station of the Saint Petersburg Metro in Russia, serving the city’s central area.
  • A. Volzhsky
    Volzhsky is a major industrial city in southwestern Russia located across the Volga River from Volgograd.
  • B. Zarechny
    Zarechny is a small Russian city in Sverdlovsk Oblast known for its role in the region’s industrial and energy sectors.
  • C. Tulskaya
    Tulskaya is a Moscow Metro station on the Serpukhovsko–Timiryazevskaya Line serving the Tulskaya Square area in southern Moscow.
  • D. Verkhnyaya Troitsa
    Verkhnyaya Troitsa is a rural locality in Russia best known as the birthplace of Soviet statesman and longtime nominal head of state Mikhail Kalinin.
  • E. Nizhegorodskaya
    Nizhegorodskaya is a Moscow Metro station on the Big Circle Line serving the Nizhegorodsky District in the southeast 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a5db9508190bbe92673ef5a7861 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bd54f548190916bf00852f37224 completed March 31, 2026, 5:29 a.m.
NEDg Description generation batch_69cb78f72878819086092c9fe267e37f completed March 31, 2026, 7:34 a.m.
NED2 Entity disambiguation (via description) batch_69cbbf2a357081908ac2230f0dfd9cdc completed March 31, 2026, 12:33 p.m.
Created at: March 30, 2026, 5:04 p.m.