Triple

T3704127
Position Surface form Disambiguated ID Type / Status
Subject Belgian railway network E80849 entity
Predicate internationalService P11099 FINISHED
Object Eurostar E39296 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: Eurostar | Statement: [Belgian railway network, internationalService, Eurostar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurostar
Context triple: [Belgian railway network, internationalService, Eurostar]
  • A. Eurostar chosen
    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.
  • B. Thalys
    Thalys is a high-speed international train service connecting major cities in France, Belgium, the Netherlands, and Germany.
  • C. SNCF Connect
    SNCF Connect is the official digital platform and app of the French national railway company, providing online ticket booking, travel planning, and real-time information for trains and other transport services.
  • D. Intercités
    Intercités is a network of French long-distance conventional trains operated by SNCF, connecting major cities and regions across the country.
  • E. TGV Ouigo
    TGV Ouigo is a low-cost high-speed train service operated by SNCF in France, offering budget fares on selected TGV routes.
  • 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_69ad8b1793888190a5f70e4b21dc05a1 completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adc54aaac88190b775dba2513b6d4a completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4db041370819084b04e46d95ca966 completed March 14, 2026, 3:50 a.m.
Created at: March 8, 2026, 3:33 p.m.