Triple

T1092749
Position Surface form Disambiguated ID Type / Status
Subject Zurich Hauptbahnhof E24201 entity
Predicate servedBy P82 FINISHED
Object TGV Lyria E11761 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 Lyria | Statement: [Zurich Hauptbahnhof, servedBy, TGV Lyria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TGV Lyria
Context triple: [Zurich Hauptbahnhof, servedBy, TGV Lyria]
  • A. Thalys
    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. Intercités
    Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
  • D. TGV high-speed rail chosen
    TGV high-speed rail is France’s flagship high-speed train service that connects major cities and hubs, including direct links from Charles de Gaulle Airport to destinations across the country and into neighboring nations.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b99bd06c8190bce1d77b0337b07c completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac66293b5c819091eb69db328d5698 completed March 7, 2026, 5:53 p.m.
Created at: March 1, 2026, 7:42 p.m.