Triple

T17880227
Position Surface form Disambiguated ID Type / Status
Subject Danish E447062 entity
Predicate hasDialects P4251 FINISHED
Object Bornholm Danish 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: Bornholm Danish | Statement: [Danish, hasDialects, Bornholm Danish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bornholm Danish
Context triple: [Danish, hasDialects, Bornholm Danish]
  • A. Bornholmsk chosen
    Bornholmsk is the distinctive East Danish dialect spoken on the island of Bornholm, known for preserving several archaic Scandinavian linguistic features.
  • B. Bornholm
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • C. Lolland
    Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
  • D. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • E. Bømlo
    Bømlo is a large island and municipality in Vestland county, Norway, known for its rugged coastline, fishing communities, and extensive network of tunnels and bridges connecting it to the mainland.
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49c0e56bc819097649377b520de63 completed April 19, 2026, 9:10 a.m.
Created at: April 10, 2026, 10:18 a.m.