Triple

T16092418
Position Surface form Disambiguated ID Type / Status
Subject Gennevilliers E390388 entity
Predicate hasPublicTransport P1288 FINISHED
Object RER E68667 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 | Statement: [Gennevilliers, hasPublicTransport, RER]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER
Context triple: [Gennevilliers, hasPublicTransport, 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 (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_69d87f198bc48190a8b7e53ca15b7ead completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1858ed09881909bde122971d95753 completed April 17, 2026, 12:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb9550f0819092660f6c4b0d708e completed May 10, 2026, 2:21 a.m.
Created at: April 10, 2026, 4:59 a.m.