Triple

T3812030
Position Surface form Disambiguated ID Type / Status
Subject Massy-Palaiseau station E93157 entity
Predicate partOf P40 FINISHED
Object RER C southwestern branches 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 southwestern branches | Statement: [Massy-Palaiseau station, partOf, RER C southwestern branches]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: RER C southwestern branches
Context triple: [Massy-Palaiseau station, partOf, RER C southwestern branches]
  • 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 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.
  • 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 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.
  • E. 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.
  • 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_69aed96a60088190ab1df8390fffc935 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aee80faaa88190b05f8aec8aa5c44d completed March 9, 2026, 3:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc51a7c6081909eeda563a4485e87 completed March 20, 2026, 10:07 p.m.
Created at: March 9, 2026, 3:16 p.m.