Triple

T8303985
Position Surface form Disambiguated ID Type / Status
Subject Line J E194414 entity
Predicate operatedBy P86 FINISHED
Object Transilien SNCF E37920 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: Transilien SNCF | Statement: [Line J, operatedBy, Transilien SNCF]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Transilien SNCF
Context triple: [Line J, operatedBy, Transilien SNCF]
  • A. Transilien chosen
    Transilien is the suburban and regional rail network operated by SNCF that serves the Île-de-France (Greater Paris) area.
  • 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 Réseau
    SNCF Réseau is the French state-owned rail infrastructure manager responsible for operating, maintaining, and developing France’s national railway network.
  • D. SNCF Sud-Est region
    The SNCF Sud-Est region was a major operating division of the French national railway company responsible for managing and running rail services in the southeastern part of France, including key routes linking Paris with Lyon and the Mediterranean.
  • 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_69ca82e613e88190bf8139669bbd0d53 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7e8b9f6081909100d1da8a078616 completed March 31, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce4d8a7eb48190bc1bebc56a46a5b9 completed April 2, 2026, 11:05 a.m.
Created at: March 30, 2026, 5:53 p.m.