Triple

T5828451
Position Surface form Disambiguated ID Type / Status
Subject Arriva Trains Wales E129286 entity
Predicate parentCompany P254 FINISHED
Object Arriva 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 | Statement: [Arriva Trains Wales, parentCompany, Arriva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arriva
Context triple: [Arriva Trains Wales, parentCompany, Arriva]
  • A. Arriva chosen
    Arriva is a major European public transport company that operates bus, coach, train, tram, and waterbus services across multiple countries.
  • B. 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.
  • C. Busbridge
    Busbridge is a small village in Surrey, England, situated near the town of Godalming and known for its rural character and historic church.
  • D. Optibús
    Optibús is the bus rapid transit (BRT) system serving the city of León in the Mexican state of Guanajuato.
  • E. 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.
  • 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_69c00849d55481908b4f9f5543e0bf6d completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c03467dfe48190b51757b33681bc20 completed March 22, 2026, 6:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c09863be3c8190bba357bf64e22917 completed March 23, 2026, 1:33 a.m.
Created at: March 22, 2026, 3:53 p.m.