Triple

T1901938
Position Surface form Disambiguated ID Type / Status
Subject High Speed 1 E37707 entity
Predicate enablesServiceBetween P6304 FINISHED
Object London and Brussels E206256 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: London and Brussels | Statement: [High Speed 1, enablesServiceBetween, London and Brussels]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: London and Brussels
Context triple: [High Speed 1, enablesServiceBetween, London and Brussels]
  • A. London–Brussels chosen
    London–Brussels is a major international high-speed rail route linking the United Kingdom and Belgium via the Channel Tunnel.
  • B. London–Amsterdam
    London–Amsterdam is a major international rail route connecting the capital cities of the United Kingdom and the Netherlands.
  • C. Brussels, Belgium
    Brussels, Belgium is the capital city of Belgium and a major political center of Europe, hosting key institutions such as the European Union and numerous international organizations.
  • D. Paris–Brussels
    Paris–Brussels is a major international high-speed rail corridor linking the capitals of France and Belgium.
  • E. Brussels metropolitan area
    The Brussels metropolitan area is the large urban region centered on Belgium’s capital, encompassing Brussels and its surrounding municipalities and commuter towns.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb7c376208190bbf28504f1aac881 completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adf3d0d01c8190ae0c8029fead4008 completed March 8, 2026, 10:10 p.m.
Created at: March 4, 2026, 7:35 p.m.