Triple

T6724113
Position Surface form Disambiguated ID Type / Status
Subject RER line E E153469 entity
Predicate owner P347 FINISHED
Object SNCF Réseau E93156 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: SNCF Réseau | Statement: [RER line E, owner, SNCF Réseau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SNCF Réseau
Context triple: [RER line E, owner, SNCF Réseau]
  • A. SNCF Réseau chosen
    SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
  • 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. 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.
  • D. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • E. SNCF Voyageurs
    SNCF Voyageurs is the passenger rail operating division of France’s national railway company, responsible for running high-speed, regional, and commuter train 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_69c6880afb988190ad88011b48ecfcba completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d13b296c8190bf54009063032c6d completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a6e21788190b91b2102ddd62aa0 completed March 28, 2026, 12:01 a.m.
Created at: March 27, 2026, 2:08 p.m.