Triple

T21299902
Position Surface form Disambiguated ID Type / Status
Subject Aulnay-sous-Bois E525030 entity
Predicate hasTransport P1298 FINISHED
Object RER B 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 | Statement: [Aulnay-sous-Bois, hasTransport, RER B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER B
Context triple: [Aulnay-sous-Bois, hasTransport, RER B]
  • A. 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.
  • B. 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.
  • C. 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.
  • D. RER NG
    RER NG is a new-generation double-deck electric multiple unit train designed for Île-de-France’s RER network, offering higher capacity, improved accessibility, and enhanced passenger comfort.
  • E. RER Vaud
    RER Vaud is a regional express rail network in the canton of Vaud, Switzerland, providing frequent commuter and regional train services connecting local towns and cities.
  • 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385b1c548190b940ded0163ee3ca completed April 21, 2026, 8:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09bb393fb0819084444c0f9e0da842 completed May 17, 2026, 12:57 p.m.
Created at: April 16, 2026, 4:05 p.m.