Triple

T16570829
Position Surface form Disambiguated ID Type / Status
Subject TGV Lyria E402577 entity
Predicate usesRollingStock P5426 FINISHED
Object TGV POS E1186567 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: TGV POS | Statement: [TGV Lyria, usesRollingStock, TGV POS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TGV POS
Context triple: [TGV Lyria, usesRollingStock, TGV POS]
  • A. TGV POS chosen
    TGV POS is a high-speed French TGV trainset designed for international services, notably operating on routes between France, Germany, and Switzerland.
  • B. TGV inOui
    TGV inOui is SNCF’s premium high-speed train service in France, offering upgraded comfort and amenities on major routes including those served by the LGV Méditerranée line.
  • C. Bezannes TGV
    Bezannes TGV is a tram terminus and transport hub in the suburb of Bezannes serving the high-speed TGV rail connections near Reims, France.
  • D. TGV PSE
    TGV PSE is the original generation of French high-speed TGV Sud-Est trainsets that inaugurated high-speed rail service in France.
  • E. TGV
    TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and 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_69d8838648088190acf97ef11fc3f61b completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e35958d49c8190b995188240fb355b completed April 18, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ee8812c81908ef74636bf39d44a completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:16 a.m.