Triple

T10046995
Position Surface form Disambiguated ID Type / Status
Subject London–Amsterdam E207640 entity
Predicate usesOperatorBrand P32898 FINISHED
Object Eurostar E39296 NE FINISHED

How this triple was built (3 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: [London–Amsterdam, usesOperatorBrand, Eurostar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurostar
Context triple: [London–Amsterdam, usesOperatorBrand, 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. 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. TGV
    TGV is France’s high-speed intercity train service, renowned for rapid connections between major cities such as Paris and Lille.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usesOperatorBrand
Context triple: [London–Amsterdam, usesOperatorBrand, Eurostar]
  • A. operatedByBrand chosen
    Indicates that an entity (such as a service, location, or product line) is run, managed, or controlled by a particular brand.
  • B. usedBrand
    Indicates that an entity has utilized, applied, or operated a particular brand in some context.
  • C. usedBrandOf
    Indicates that one entity made use of or operated an item, product, or service associated with a particular brand.
  • D. usesBrandCharacter
    Indicates that one entity employs or features another entity’s brand character (such as a mascot or branded persona) in its materials, products, or communications.
  • E. usesTransportBrand
    Indicates that one entity makes use of a transportation service, vehicle, or system associated with a specific brand.
  • F. None of above.

Provenance (4 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf664dd881908786fcd802bf10da completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
PD Predicate disambiguation batch_69cd4b8d2280819089de27e57babd1f3 completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 8:56 p.m.