Triple

T5956319
Position Surface form Disambiguated ID Type / Status
Subject Foch E132523 entity
Predicate railwayLine P848 FINISHED
Object RER C E13072 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 C | Statement: [Foch, railwayLine, RER C]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER C
Context triple: [Foch, railwayLine, RER C]
  • A. RER C chosen
    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.
  • B. 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.
  • C. 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.
  • D. RER B line
    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.
  • E. 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.
  • 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_69c0086b05cc8190a8f36a96927a525c completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c039c1de80819085c97a0aa2d37f32 completed March 22, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0e3dd99888190ac3eeef692a7d879 completed March 23, 2026, 6:55 a.m.
Created at: March 22, 2026, 4:02 p.m.