Triple

T581101
Position Surface form Disambiguated ID Type / Status
Subject Paris airport system E15058 entity
Predicate hasRailConnection P848 FINISHED
Object RER B line E10905 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: RER B line | Statement: [Paris airport system, hasRailConnection, RER B line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER B line
Context triple: [Paris airport system, hasRailConnection, RER B line]
  • A. RER B line chosen
    The RER B line is a major Paris regional express railway line that connects central Paris with key northern and southern suburbs, including Charles de Gaulle Airport.
  • B. RER A
    RER A is one of the main lines of the Paris regional express network, carrying large volumes of commuters and travelers between central Paris and its suburbs.
  • C. RER network
    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.
  • 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 D
    RER D is one of the main lines of the Paris regional express network (RER), connecting northern and southern suburbs through central Paris.
  • 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_69a4935783b8819082b77726ec10cc42 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a49b84899881909d5b2b4e67e22d9b completed March 1, 2026, 8:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69a518c44ef0819088048289ed31246f completed March 2, 2026, 4:57 a.m.
Created at: March 1, 2026, 7:33 p.m.