Triple

T16771235
Position Surface form Disambiguated ID Type / Status
Subject Lyon-Saint Exupéry TGV station E407599 entity
Predicate servesTrainType P21523 FINISHED
Object Ouigo E90447 NE FINISHED

How this triple was built (2 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: Ouigo | Statement: [Lyon-Saint Exupéry TGV station, servesTrainType, Ouigo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ouigo
Context triple: [Lyon-Saint Exupéry TGV station, servesTrainType, Ouigo]
  • A. Ouigo chosen
    Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard services.
  • B. Bezannes TGV
    Bezannes TGV is a tram terminus and transport hub in the suburb of Bezannes serving the high-speed TGV rail connections near Reims, France.
  • C. TGV Ouigo
    TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
  • D. OUIGO
    OUIGO is a low-cost high-speed train service operated by France’s national railway company SNCF, offering budget-friendly travel on major routes.
  • E. TGV
    TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0361e5081908f58edf766ff3ce0 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aafa19888190bb7f96591f363867 completed May 10, 2026, 3:57 p.m.
Created at: April 10, 2026, 5:21 a.m.