Triple

T5313087
Position Surface form Disambiguated ID Type / Status
Subject Arriva E119079 entity
Predicate hasSubsidiary P254 FINISHED
Object Arriva Netherlands E119079 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: Arriva Netherlands | Statement: [Arriva, hasSubsidiary, Arriva Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arriva Netherlands
Context triple: [Arriva, hasSubsidiary, Arriva Netherlands]
  • A. Arriva chosen
    Arriva is a major European public transport company that operates bus, coach, train, tram, and waterbus services across multiple countries.
  • B. Arvato
    Arvato is a global business process outsourcing and services provider specializing in customer relationship management, supply chain management, and digital solutions.
  • C. Abellio
    Abellio is a Dutch-based public transport company that operates train and bus services in the United Kingdom and parts of Europe.
  • D. Arriva UK Trains
    Arriva UK Trains is a major British train operating company that manages several passenger rail franchises and services across the United Kingdom.
  • E. Arriva Trains Northern
    Arriva Trains Northern was a former British train operating company that provided regional and commuter rail services across Northern England.
  • 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_69bd446b57bc8190a513d2e6c40314f3 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd8536c06c81908ef8ba8c39b4fa30 completed March 20, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf1106ef9c8190811f7b70e784c962 completed March 21, 2026, 9:43 p.m.
Created at: March 20, 2026, 1:54 p.m.