Triple

T10011922
Position Surface form Disambiguated ID Type / Status
Subject Sadovaya metro station E199393 entity
Predicate line P1293 FINISHED
Object Line 5
Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
E834773 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: Line 5 | Statement: [Sadovaya metro station, line, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Sadovaya metro station, line, Line 5]
  • A. Line 5
    Line 5 is a major north–south route of the Beijing Subway known for connecting key residential and commercial areas through the city center.
  • B. Line 5
    Line 5 is a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • C. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • D. Line 5
    Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
  • E. Line 5
    Line 5 is a major east–west rapid transit line of the Seoul Metropolitan Subway system in South Korea, serving key districts across the city and extending into surrounding areas.
  • 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: Line 5
Triple: [Sadovaya metro station, line, Line 5]
Generated description
Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
  • A. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
  • B. Line 5
    Line 5 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving as one of the city's key urban rail corridors.
  • C. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • D. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • E. Line 5
    Line 5 is a major east–west rapid transit line of the Seoul Metropolitan Subway system in South Korea, serving key districts across the city and extending into surrounding areas.
  • 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_69ca8315a1a08190ab310f25620f362b completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cdcd3cf5b881908f5318e55bdd22b6 completed April 2, 2026, 1:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69d26a7b0ce08190b6109ddbc0b05362 completed April 5, 2026, 1:58 p.m.
NEDg Description generation batch_69d26b6d52e8819082fed0bfdaf48e4c completed April 5, 2026, 2:02 p.m.
NED2 Entity disambiguation (via description) batch_69d26c47d25081908818f18f6b0881b2 completed April 5, 2026, 2:06 p.m.
Created at: March 30, 2026, 8:52 p.m.