Triple

T5036674
Position Surface form Disambiguated ID Type / Status
Subject HSL-Zuid E113440 entity
Predicate usedByService P1294 FINISHED
Object Thalys E38855 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: Thalys | Statement: [HSL-Zuid, usedByService, Thalys]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thalys
Context triple: [HSL-Zuid, usedByService, Thalys]
  • A. Thalys chosen
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • B. Eurostar
    Eurostar is a high-speed international train service connecting the United Kingdom with mainland Europe via the Channel Tunnel, linking cities such as London, Paris, and Brussels.
  • C. TGV Lyria
    TGV Lyria is a high-speed train service linking France and Switzerland, operated as a joint venture between SNCF and Swiss Federal Railways.
  • D. Paris–Amsterdam high-speed corridor
    The Paris–Amsterdam high-speed corridor is a major European rail axis linking France, Belgium, and the Netherlands via high-speed lines that enable fast passenger services between Paris and Amsterdam.
  • E. Ouigo
    Ouigo is a low-cost high-speed train service operated by France's SNCF, offering budget TGV travel with simplified onboard services.
  • 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_69bd44384298819089c49e7c330ec7b8 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd73bb069c8190af86f1b2f95f3d95 completed March 20, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be9c79265081908512b39cc74161f8 completed March 21, 2026, 1:26 p.m.
Created at: March 20, 2026, 1:37 p.m.