Triple

T22557831
Position Surface form Disambiguated ID Type / Status
Subject Trans Europ Express E557733 entity
Predicate memberOperator P148650 FINISHED
Object Danish State Railways NE NERFINISHED

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: Danish State Railways | Statement: [Trans Europ Express, memberOperator, Danish State Railways]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Danish State Railways
Context triple: [Trans Europ Express, memberOperator, Danish State Railways]
  • A. Danske Statsbaner chosen
    Danske Statsbaner is Denmark’s largest state-owned railway company, responsible for most passenger train services across the country.
  • B. Norwegian State Railways
    Norwegian State Railways was Norway’s former government-owned railway company responsible for most passenger train services and rail operations across the country.
  • C. Finland Railway
    Finland Railway was a historical railway company that operated key lines in the Russian Empire, including the route terminating at Saint Petersburg’s Finland Station.
  • D. Metro Service A/S
    Metro Service A/S is the company responsible for operating and managing the Copenhagen Metro system in Denmark.
  • E. Aarhus Letbane
    Aarhus Letbane is a light rail transit system serving the city of Aarhus and surrounding areas in Denmark.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e59db848190b4272ecd2b690ffd completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15f7b06e08190b3ca82a783965942 completed April 29, 2026, 1:31 a.m.
Created at: April 16, 2026, 8:52 p.m.