Triple

T7518164
Position Surface form Disambiguated ID Type / Status
Subject Marne-la-Vallée–Chessy station E177697 entity
Predicate railNetwork P522 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: [Marne-la-Vallée–Chessy station, railNetwork, OUIGO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OUIGO
Context triple: [Marne-la-Vallée–Chessy station, railNetwork, OUIGO]
  • A. 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.
  • B. SNCF Réseau
    SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
  • C. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • D. 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.
  • E. Ouigo chosen
    Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard 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_69c69f2891148190a484f3b8222c6f1b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5f850c081909e697219071293fc completed March 27, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8462610b481909fa74023852b0154 completed March 28, 2026, 9:20 p.m.
Created at: March 27, 2026, 3:46 p.m.