Triple

T20099081
Position Surface form Disambiguated ID Type / Status
Subject Lyon tramway network E496483 entity
Predicate hasLine P35 FINISHED
Object T3
T3 is a tram line in the Lyon public transport system that connects the city center with eastern suburbs and key hubs such as Part-Dieu station and Parc Olympique Lyonnais.
 E487752 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: T3 | Statement: [Lyon tramway network, hasLine, T3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: T3
Context triple: [Lyon tramway network, hasLine, T3]
  • A. T3
    T3 is a tram line within the Casablanca Tramway network that serves as one of the city’s main urban light rail routes.
  • B. T3
    T3 is an American rapper best known as a founding member of the influential Detroit hip hop group Slum Village.
  • C. T3
    T3 is a TrawsCymru long-distance bus service route operating in Wales as part of the national TrawsCymru network.
  • D. T3
    T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
  • E. T3
    T3 is one of the main lines of the Athens tram system, providing light rail service that connects key coastal and urban areas of the city.
  • 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: T3
Triple: [Lyon tramway network, hasLine, T3]
Generated description
T3 is a tram line in the Lyon public transport system that connects the city center with eastern suburbs and key hubs such as Part-Dieu station and Parc Olympique Lyonnais.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: T3
Target entity description: T3 is a tram line in the Lyon public transport system that connects the city center with eastern suburbs and key hubs such as Part-Dieu station and Parc Olympique Lyonnais.
  • A. T3 chosen
    T3 is a tram line in the Lyon public transport network in France, connecting the city center with eastern suburbs and key hubs like Part-Dieu station and the Eurexpo exhibition center.
  • B. T3
    T3 is one of the main lines of the Athens tram system, providing light rail service that connects key coastal and urban areas of the city.
  • C. T3
    T3 is a tram line within the Casablanca Tramway network that serves as one of the city’s main urban light rail routes.
  • D. T3
    T3 is one of the tram lines of the Trambaix light rail network serving the Barcelona metropolitan area.
  • E. T3
    T3 is a TrawsCymru long-distance bus service route operating in Wales as part of the national TrawsCymru network.
  • F. None of above.

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_69da626eee3881909f3454986d4a6511 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6666e306c81909c0ef617e0f6fccf completed April 20, 2026, 5:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08270edd6481909230ece4487f93fd completed May 16, 2026, 8:13 a.m.
NEDg Description generation batch_6a0827c6a68c8190aed2d531b4fd2030 completed May 16, 2026, 8:16 a.m.
NED2 Entity disambiguation (via description) batch_6a08288d98fc8190a146f43a027682f0 completed May 16, 2026, 8:19 a.m.
Created at: April 11, 2026, 11:26 p.m.