Triple

T20499979
Position Surface form Disambiguated ID Type / Status
Subject Lyon urban transport network E503273 entity
Predicate connectsTo P845 FINISHED
Object Gare de Vaise NE NERFINISHED

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: Gare de Vaise | Statement: [Lyon urban transport network, connectsTo, Gare de Vaise]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gare de Vaise
Context triple: [Lyon urban transport network, connectsTo, Gare de Vaise]
  • A. Gare de Vaise chosen
    Gare de Vaise is a major transport hub and metro terminus in Lyon, France, serving the northwestern part of the city.
  • B. Gare de Vénissieux
    Gare de Vénissieux is a major transport hub in the Lyon metropolitan area, serving as both a railway station and a key terminus for the city’s metro and tram networks.
  • C. Gare de Colombes
    Gare de Colombes is a suburban railway station in Colombes, France, serving regional commuter trains in the Paris metropolitan area.
  • D. Gare d’Oullins
    Gare d’Oullins is a railway and metro station in the suburb of Oullins near Lyon, France, serving as a key public transport hub integrated into the Lyon Metro network.
  • E. Gare de Javel
    Gare de Javel is a Parisian commuter rail station in the 15th arrondissement that serves local and regional passengers along the Seine.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b1e52c8190894281cf7e3283ab completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e69cc10cd08190915b6c29c6473f77 completed April 20, 2026, 9:38 p.m.
Created at: April 16, 2026, 11:35 a.m.