Triple

T2142546
Position Surface form Disambiguated ID Type / Status
Subject Paris Orly Airport E46790 entity
Predicate connectedBy P37 FINISHED
Object Orlyval automated metro E14727 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: Orlyval automated metro | Statement: [Paris Orly Airport, connectedBy, Orlyval automated metro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orlyval automated metro
Context triple: [Paris Orly Airport, connectedBy, Orlyval automated metro]
  • A. Orlyval chosen
    Orlyval is an automated light rail shuttle service in the Paris region that links Orly Airport to the broader RER and metro network.
  • B. Alweg Monorail
    The Alweg Monorail is an elevated monorail system in Seattle that became an iconic symbol of mid-20th-century futuristic transportation design.
  • C. Metrocars
    Metrocars are the electric multiple unit trains specifically designed and used for passenger services on the Tyne and Wear Metro system in North East England.
  • D. Montreal Metro
    The Montreal Metro is the rubber-tired rapid transit system serving the city of Montreal and its surrounding areas, known for its extensive underground network and distinctively designed stations.
  • E. AeroTrain
    AeroTrain is an automated underground people mover system that transports passengers between terminals at Washington Dulles International Airport.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe206db0819095772af5358dca55 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b63e4081908a5d87af5d17d3c4 completed March 9, 2026, 4:51 a.m.
Created at: March 4, 2026, 7:44 p.m.