Triple

T5339714
Position Surface form Disambiguated ID Type / Status
Subject Line 5 Eglinton E123914 entity
Predicate shortName P43 FINISHED
Object Line 5
Line 5 is a planned light rail transit line in Toronto’s Eglinton Avenue corridor that will form part of the city’s rapid transit network.
E512349 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: [Line 5 Eglinton, shortName, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [Line 5 Eglinton, shortName, Line 5]
  • A. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • B. 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.
  • C. 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.
  • D. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • E. 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.
  • 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: [Line 5 Eglinton, shortName, Line 5]
Generated description
Line 5 is a planned light rail transit line in Toronto’s Eglinton Avenue corridor that will form 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 a planned light rail transit line in Toronto’s Eglinton Avenue corridor that will form part of the city’s rapid transit network.
  • A. Line 5
    Line 5 is a planned rapid transit route of the Ho Chi Minh City Metro system intended to serve as part of the city’s future urban rail network.
  • 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 a major east–west rapid transit route in the Guangzhou Metro system, serving key urban districts and facilitating high-capacity cross-city travel.
  • D. 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.
  • E. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs 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_69bd464b07f8819095aa76577c9829e4 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd85c9cff48190900d234a7569cd5d completed March 20, 2026, 5:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18c54ca4819095ca1d81ee061937 completed March 21, 2026, 10:16 p.m.
NEDg Description generation batch_69bf1977edd481909cb4ab25f58fd64b completed March 21, 2026, 10:19 p.m.
NED2 Entity disambiguation (via description) batch_69bf19d2a0bc8190b594fafbb1e540a6 completed March 21, 2026, 10:21 p.m.
Created at: March 20, 2026, 2 p.m.