Triple

T17070929
Position Surface form Disambiguated ID Type / Status
Subject SNCF TER E414215 entity
Predicate formerName P65 FINISHED
Object Transport Express Régional E206983 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: Transport Express Régional | Statement: [SNCF TER, formerName, Transport Express Régional]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transport Express Régional
Context triple: [SNCF TER, formerName, Transport Express Régional]
  • A. Transport Express Régional chosen
    Transport Express Régional is a network of regional passenger trains in France operated by SNCF, providing local and intercity rail services across most French regions.
  • B. Intercités
    Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
  • 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 Réseau
    TGV Réseau is a later-generation French high-speed trainset used by SNCF, designed for improved performance and comfort on the expanding TGV network.
  • E. 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.
  • 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_69d886cef44c8190ba56c44b4e863e64 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dbc0982c8190916f9905ddb5e575 completed April 18, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012edbce988190a784448ba8a258a5 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:34 a.m.