Triple

T7970366
Position Surface form Disambiguated ID Type / Status
Subject Chessy, France E185306 entity
Predicate servedBy P82 FINISHED
Object RER A line E43969 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 A line | Statement: [Chessy, France, servedBy, RER A line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: RER A line
Context triple: [Chessy, France, servedBy, RER A line]
  • A. RER A chosen
    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
    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 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.
  • D. RER line E
    RER line E is a Paris regional express railway line connecting central Paris with eastern suburbs such as Gagny.
  • E. RER line D
    RER line D is one of the main lines of the Paris RER suburban rail network, running north–south through central Paris and serving numerous suburbs across the Île-de-France region.
  • 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_69ca8297699481909b75a405f01e03af completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3bd304dc8190b9feee5e17fc66db completed March 31, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe0aadcc48190ae35154195099029 completed March 31, 2026, 2:56 p.m.
Created at: March 30, 2026, 5:13 p.m.