Triple

T8456913
Position Surface form Disambiguated ID Type / Status
Subject British Rail Class 373 E199940 entity
Predicate operator P179 FINISHED
Object Eurostar UK 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 UK | Statement: [British Rail Class 373, operator, Eurostar UK]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eurostar UK
Context triple: [British Rail Class 373, operator, Eurostar UK]
  • 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. Eurotunnel Shuttle
    Eurotunnel Shuttle is a rail freight and passenger shuttle service that carries vehicles and their occupants through the Channel Tunnel between the United Kingdom and France.
  • D. Francorail
    Francorail was a French railway manufacturing consortium known for producing high-speed trainsets, including early models of the TGV.
  • E. Virgin Trains
    Virgin Trains was a British train operating company under Richard Branson’s Virgin Group brand that ran long-distance passenger rail services in the UK.
  • 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_69ca8318231881908fd1bc1c4d45d286 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe48f180c8190a71cf9d7248ade60 completed March 31, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea82c897c8190b7554d2e91968b53 completed April 2, 2026, 5:32 p.m.
Created at: March 30, 2026, 6:10 p.m.