Triple

T20941507
Position Surface form Disambiguated ID Type / Status
Subject TAN public transport network E515732 entity
Predicate hasTramLine P17788 FINISHED
Object Line 3 — NE NERFINISHED

How this triple was built (3 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: [TAN public transport network, hasTramLine, Line 3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 3
Context triple: [TAN public transport network, hasTramLine, Line 3]
  • A. Line 3
    Line 3 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • B. Line 3
    Line 3 is a major rapid transit route of the Guangzhou Metro system, known for its high passenger volume and key role in connecting central urban areas with the airport and suburban districts.
  • C. Line 3
    Line 3 is a future rapid transit route of the Seville Metro intended to extend and improve the city’s urban rail network.
  • D. 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.
  • E. Line 3
    Line 3 is a rapid transit line of the Shijiazhuang Metro system in Shijiazhuang, Hebei, China.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 3
Target entity description: Line 3 is a tram route within Nantes’ TAN public transport network, serving key corridors across the city.
  • A. Line 3
    Line 3 is a major trolleybus route within Geneva’s public transport system, connecting key districts of the city.
  • 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 one of the light rail routes of the Tunis Metro system, serving urban districts within the Tunis metropolitan area.
  • D. Line 3
    Line 3 is a major route within the Linz tramway network in Austria, providing urban public transport across key parts of the city.
  • E. Line 3
    Line 3 is a rapid transit route of the Nanjing Metro system in Nanjing, China, serving as one of the city's main north–south subway lines.
  • F. None of above. chosen

Provenance (2 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_69e0b4fc13408190b06868df03c5c29b completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6f955f0148190ae42278ad5c0f363 completed April 21, 2026, 4:13 a.m.
Created at: April 16, 2026, 12:50 p.m.