Triple

T16847407
Position Surface form Disambiguated ID Type / Status
Subject TGV Atlantique services E409579 entity
Predicate primaryCorridor P3034 FINISHED
Object Paris–Nantes E873647 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: Paris–Nantes | Statement: [TGV Atlantique services, primaryCorridor, Paris–Nantes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paris–Nantes
Context triple: [TGV Atlantique services, primaryCorridor, Paris–Nantes]
  • A. Paris–Nantes chosen
    Paris–Nantes is a major high-speed rail corridor in France linking the capital Paris with the western city of Nantes.
  • 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–Bordeaux
    Paris–Bordeaux is a major high-speed rail corridor in France connecting the capital with the southwest, known for its fast TGV services.
  • D. Paris–Granville
    Paris–Granville is a regional railway service in France connecting the capital city Paris with the coastal town of Granville in Normandy.
  • E. Paris–Lille
    Paris–Lille is a major high-speed rail corridor in northern France connecting the capital Paris with the city of Lille.
  • 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_69d883952b048190887740a980b712ed completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b376bac48190ae09f29a28c55f8c completed April 18, 2026, 4:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c2a4c2a881908d2797f6e61792d3 completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:24 a.m.