Triple

T17840321
Position Surface form Disambiguated ID Type / Status
Subject TGV E445505 entity
Predicate route P5619 FINISHED
Object Paris–Lyon 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: Paris–Lyon | Statement: [TGV, route, Paris–Lyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris–Lyon
Context triple: [TGV, route, Paris–Lyon]
  • A. Paris–Lyon chosen
    Paris–Lyon is the pioneering high-speed rail corridor in France that became the flagship route for TGV operations between the capital and the major southeastern city.
  • B. Paris–Marseille
    Paris–Marseille is a major French intercity rail corridor linking the capital Paris with the Mediterranean port city of Marseille.
  • C. Paris–Dijon
    Paris–Dijon is a major French high-speed rail corridor linking the capital Paris with the historic city of Dijon, serving as part of international routes toward Switzerland and beyond.
  • D. Paris–Strasbourg
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • E. Paris–Nantes
    Paris–Nantes is a major high-speed rail corridor in France linking the capital Paris with the western city of Nantes.
  • 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_69d8b9f1a6d881909f024bc603111cdb completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48d2b2ea08190926ec0cf01285833 completed April 19, 2026, 8:07 a.m.
Created at: April 10, 2026, 10:16 a.m.