Triple

T10541128
Position Surface form Disambiguated ID Type / Status
Subject TGV Ouigo E248696 entity
Predicate notableRoute P22 FINISHED
Object Paris–Strasbourg E88047 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–Strasbourg | Statement: [TGV Ouigo, notableRoute, Paris–Strasbourg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris–Strasbourg
Context triple: [TGV Ouigo, notableRoute, Paris–Strasbourg]
  • A. Paris–Strasbourg chosen
    Paris–Strasbourg is a major high-speed rail corridor in France linking the capital with the Alsatian city near the German border.
  • 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–Luxembourg
    Paris–Luxembourg is a major international railway route linking the French capital Paris with the Grand Duchy of Luxembourg.
  • D. Paris–Mulhouse route
    The Paris–Mulhouse route is a major French transport corridor linking the capital Paris with the eastern city of Mulhouse, serving as an important axis for regional and international traffic.
  • E. Paris–Metz–Nancy
    Paris–Metz–Nancy is a major French intercity rail route linking the capital Paris with the northeastern cities of Metz and Nancy.
  • 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_69d381c733c08190ab1dd6239f5f34ae completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d50a5918648190b16c2d1bc1bf015f completed April 7, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69d96b474a248190b46c31e8e0008f9f completed April 10, 2026, 9:27 p.m.
Created at: April 6, 2026, 12:32 p.m.