Triple

T4909577
Position Surface form Disambiguated ID Type / Status
Subject Lille-Europe station E110198 entity
Predicate servesTrainOperator P782 FINISHED
Object Ouigo (some services) 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 (some services) | Statement: [Lille-Europe station, servesTrainOperator, Ouigo (some services)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ouigo (some services)
Context triple: [Lille-Europe station, servesTrainOperator, Ouigo (some services)]
  • 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. SNCF Connect
    SNCF Connect is the official digital platform and app of the French national railway company, providing online ticket booking, travel planning, and real-time information for trains and other transport services.
  • 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. TGV services
    TGV services are France’s high-speed train operations, providing fast intercity and international rail connections across the country and beyond.
  • E. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • 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_69bd44132b94819088522d92beaadc78 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6e99414081908c3d3283f563bba4 completed March 20, 2026, 3:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6fe43a888190ab1b150da0f49203 completed March 21, 2026, 10:16 a.m.
Created at: March 20, 2026, 1:29 p.m.