Triple

T17827780
Position Surface form Disambiguated ID Type / Status
Subject TGV Réseau E445164 entity
Predicate operator P179 FINISHED
Object SNCF Voyages NE NERFINISHED

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: SNCF Voyages | Statement: [TGV Réseau, operator, SNCF Voyages]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SNCF Voyages
Context triple: [TGV Réseau, operator, SNCF Voyages]
  • A. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • B. SNCF
    SNCF is France’s national state-owned railway company, responsible for operating the country’s passenger and freight rail services and much of its rail infrastructure.
  • C. 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.
  • D. SNCF Voyageurs chosen
    SNCF Voyageurs is the passenger rail operating division of France’s national railway company, responsible for running high-speed, regional, and commuter train services.
  • 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 (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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48915d0fc819080ab03feb2465834 completed April 19, 2026, 7:49 a.m.
Created at: April 10, 2026, 10:15 a.m.