Triple

T5014201
Position Surface form Disambiguated ID Type / Status
Subject Rhônexpress E112700 entity
Predicate terminus P388 FINISHED
Object Lyon Part-Dieu E20605 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: Lyon Part-Dieu | Statement: [Rhônexpress, terminus, Lyon Part-Dieu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lyon Part-Dieu
Context triple: [Rhônexpress, terminus, Lyon Part-Dieu]
  • A. Quartier Part-Dieu
    Quartier Part-Dieu is Lyon’s main business district, known for its high-rise offices, major shopping center, and one of France’s busiest railway stations.
  • B. La Part-Dieu
    La Part-Dieu is a major business and commercial district in Lyon, France, known for its large shopping center, office towers, and central train station.
  • C. Lyon-Part-Dieu railway station chosen
    Lyon-Part-Dieu railway station is a major high-speed and regional rail hub in Lyon, France, serving as one of the country’s busiest and most important transport interchanges.
  • D. Châtelet–Les Halles
    Châtelet–Les Halles is a major underground transport hub in central Paris, serving as one of the largest and busiest railway and metro stations in Europe.
  • E. Lyon-Perrache station
    Lyon-Perrache station is one of Lyon’s main railway hubs, serving regional, national, and international train connections in southeastern France.
  • 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_69bd4434acb8819086679dbeccc2fe54 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd7310c5b08190a5c9ab0f9fe9569f completed March 20, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69bea473a1708190aaf4a021fec472c6 completed March 21, 2026, 2 p.m.
Created at: March 20, 2026, 1:35 p.m.