Triple

T1847172
Position Surface form Disambiguated ID Type / Status
Subject Volgograd Metrotram E41308 entity
Predicate hasStation P35 FINISHED
Object Yuzhnaya station
Yuzhnaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
 E239866 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: Yuzhnaya station | Statement: [Volgograd Metrotram, hasStation, Yuzhnaya station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Yuzhnaya station
Context triple: [Volgograd Metrotram, hasStation, Yuzhnaya station]
  • A. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Komsomolskaya station
    Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Yelshanka station
    Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • D. Traktorozavodskaya station
    Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
  • E. Chistye Prudy station
    Chistye Prudy station is a Moscow Metro station in the city center, known for its early Soviet architecture and location near the historic Clean Ponds area.
  • 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: Yuzhnaya station
Triple: [Volgograd Metrotram, hasStation, Yuzhnaya station]
Generated description
Yuzhnaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Yuzhnaya station
Target entity description: Yuzhnaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • A. Khimvolokno station
    Khimvolokno station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • B. Komsomolskaya station
    Komsomolskaya station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • C. Yelshanka station
    Yelshanka station is a stop on the Volgograd Metrotram light rail system in Volgograd, Russia.
  • D. Traktorozavodskaya station
    Traktorozavodskaya station is a stop on Volgograd’s Metrotram system serving the industrial Traktorozavodsky district of the city.
  • E. Chistye Prudy station
    Chistye Prudy station is a Moscow Metro station in the city center, known for its early Soviet architecture and location near the historic Clean Ponds area.
  • 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_69a88648cd44819093303206d96d76ad completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb052e0a8819091bbc0da0e0a20fb completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae58b4c9ac8190b9b54dc08f9440bf completed March 9, 2026, 5:20 a.m.
NEDg Description generation batch_69ae599c6b288190b7e173ffc505c605 completed March 9, 2026, 5:24 a.m.
NED2 Entity disambiguation (via description) batch_69ae5a42675c8190a019034e8a6bda21 completed March 9, 2026, 5:27 a.m.
Created at: March 4, 2026, 7:33 p.m.