Triple

T4173215
Position Surface form Disambiguated ID Type / Status
Subject Robinson station E86411 entity
Predicate servedByLine P1293 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: [Robinson station, servedByLine, RER B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER B
Context triple: [Robinson station, servedByLine, 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 line E
    RER line E is a Paris regional express railway line connecting central Paris with eastern suburbs such as Gagny.
  • 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_69aed93de98c8190ad838ce507b77c8a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02e65b548190be095df62091b960 completed March 9, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4d60ae3c8190aea53073a37d0c07 completed March 21, 2026, 7:48 a.m.
Created at: March 9, 2026, 3:45 p.m.