Triple

T9826900
Position Surface form Disambiguated ID Type / Status
Subject Krems an der Donau E238677 entity
Predicate twinTown P1072 FINISHED
Object Roskilde, Denmark E268221 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: Roskilde, Denmark | Statement: [Krems an der Donau, twinTown, Roskilde, Denmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Roskilde, Denmark
Context triple: [Krems an der Donau, twinTown, Roskilde, Denmark]
  • A. Roskilde chosen
    Roskilde is a historic Danish city on the island of Zealand, known for its medieval cathedral and the annual Roskilde music festival.
  • B. Billund, Denmark
    Billund, Denmark is a small Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
  • C. Farum, Denmark
    Farum, Denmark is a suburban town in Furesø Municipality on the island of Zealand, known for its residential character and proximity to Copenhagen.
  • D. Frederiksberg, Denmark
    Frederiksberg, Denmark is an affluent, centrally located municipality within the Copenhagen urban area, known for its green parks, cultural institutions, and residential character.
  • E. Aabenraa, Denmark
    Aabenraa, Denmark is a coastal town in Southern Jutland near the German border, known for its historic harbor, maritime heritage, and role as a regional commercial center.
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb324e7848190b9424a78ca653afe completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1cc88a86c819088f259a049eec4db completed April 5, 2026, 2:44 a.m.
Created at: March 30, 2026, 8:32 p.m.