Triple

T11254642
Position Surface form Disambiguated ID Type / Status
Subject Sauwerd E266405 entity
Predicate servedByTrainOperator P20222 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: [Sauwerd, servedByTrainOperator, Arriva Netherlands]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arriva Netherlands
Context triple: [Sauwerd, servedByTrainOperator, Arriva Netherlands]
  • A. Arriva Poland
    Arriva Poland is a Polish public transport operator providing bus and rail services as part of the wider Arriva Group’s European operations.
  • B. Arriva chosen
    Arriva is a major European public transport company that operates bus, coach, train, tram, and waterbus services across multiple countries.
  • C. Arriva Czech Republic
    Arriva Czech Republic is a public transport operator in the Czech Republic, providing bus and rail services as part of the international Arriva group.
  • D. Arriva Croatia
    Arriva Croatia is a Croatian public transport operator providing regional and intercity bus services as part of the wider European Arriva Group.
  • E. Govia
    Govia is a major British train operating company formed as a joint venture between the Go-Ahead Group and Keolis, running several rail franchises in the United Kingdom.
  • 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_69d6aac7953c8190b82caf9d7640fdf9 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9346f4c8190b29c2cf3a29cd1d1 completed April 9, 2026, 6 p.m.
NED1 Entity disambiguation (via context triple) batch_69e4cc941d34819099ae30713bdd03e5 completed April 19, 2026, 12:37 p.m.
Created at: April 8, 2026, 9:31 p.m.