Triple

T6811942
Position Surface form Disambiguated ID Type / Status
Subject Line 3 of Saint Petersburg Metro E156654 entity
Predicate alternativeName P39 FINISHED
Object Line 3
Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
 E622368 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 3 | Statement: [Line 3 of Saint Petersburg Metro, alternativeName, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 3
Context triple: [Line 3 of Saint Petersburg Metro, alternativeName, Line 3]
  • A. Line 3
    Line 3 is a major north–south route of the Tehran Metro system, connecting key residential and commercial areas across the city.
  • B. Line 3
    Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
  • C. Line 3
    Line 3 is a rapid transit line of the Toronto subway system, commonly known as the Scarborough RT, that served the Scarborough district.
  • D. Line 3
    Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
  • E. Line 3
    Line 3 is a major north–south route of the Seoul Metropolitan Subway system, connecting key residential and commercial districts across the city and 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 3
Triple: [Line 3 of Saint Petersburg Metro, alternativeName, Line 3]
Generated description
Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 3
Target entity description: Line 3 is a major line of the Saint Petersburg Metro system, serving as one of the city's primary rapid transit routes.
  • A. Line 3
    Line 3 is a major line of the Moscow Metro system, known for serving central Moscow and connecting key residential and commercial districts.
  • B. Line 3
    Line 3 is a major rapid transit route of the STC Metro system, serving key districts along its corridor.
  • C. Line 3
    Line 3 is a major north–south rapid transit route of the Shanghai Metro system, known for its elevated tracks and extensive coverage across the city.
  • D. Line 3
    Line 3 is one of the main lines of the Barcelona Metro system, running through central parts of the city and connecting several key stations and neighborhoods.
  • E. Line 3
    Line 3 is a major north–south route of the Seoul Metropolitan Subway system, connecting key residential and commercial districts across the city and 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_69c68828b26c819090fe9df7612bbc27 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d329861881909f65bd1017ea384b completed March 27, 2026, 6:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723d775a48190bfdf5b6a52339833 completed March 28, 2026, 12:41 a.m.
NEDg Description generation batch_69c724a4f64481908676d15a09e9db28 completed March 28, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69c725814d188190bd158292b34a553f completed March 28, 2026, 12:49 a.m.
Created at: March 27, 2026, 2:16 p.m.