Triple

T20456370
Position Surface form Disambiguated ID Type / Status
Subject RER Vaud E501798 entity
Predicate networkType P3937 FINISHED
Object RER 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: RER | Statement: [RER Vaud, networkType, RER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER
Context triple: [RER Vaud, networkType, RER]
  • A. RER D
    RER D is one of the main lines of the Paris regional express network (RER), connecting northern and southern suburbs through central Paris.
  • B. RER E
    RER E is a line of the Paris express suburban rail network (Réseau Express Régional) serving eastern suburbs and connecting them to central Paris.
  • C. Nation (RER)
    Nation (RER) is a major Paris RER station and transport hub located at Place de la Nation in the 11th and 12th arrondissements.
  • D. RER C
    RER C is a major line of the Paris regional express rail network that connects central Paris with several suburbs and key destinations, including access to Orly Airport.
  • E. RER network chosen
    The RER network is a rapid transit system of express suburban trains serving Paris and its surrounding metropolitan area, integrating both urban and regional rail 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a1b03c8190984d9db6d3251308 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:32 a.m.