Triple

T5330138
Position Surface form Disambiguated ID Type / Status
Subject Bornholmsk E123284 entity
Predicate spokenIn P2266 FINISHED
Object Bornholm E23381 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: Bornholm | Statement: [Bornholmsk, spokenIn, Bornholm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bornholm
Context triple: [Bornholmsk, spokenIn, Bornholm]
  • A. Bornholm chosen
    Bornholm is a Danish island known for its rocky coastline, medieval ruins, and picturesque fishing villages in the Baltic Sea.
  • B. Lolland
    Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
  • C. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • D. Møn
    Møn is a Danish island in the Baltic Sea known for its dramatic white chalk cliffs, scenic landscapes, and rich prehistoric and cultural heritage.
  • E. North Jutlandic Island
    North Jutlandic Island is a large island in northern Denmark separated from the rest of Jutland by the Limfjord and known for its coastal landscapes and tourism.
  • 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_69bd46477f9081909d242a327d749466 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd859552d8819080758bdd7c43c66a completed March 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf18b396c08190be60bcb9ac933b5e completed March 21, 2026, 10:16 p.m.
Created at: March 20, 2026, 2 p.m.