Triple

T1188170
Position Surface form Disambiguated ID Type / Status
Subject Nielsen E25294 entity
Predicate hasRegionOfPrevalence P22713 FINISHED
Object Denmark E5474 NE FINISHED

How this triple was built (3 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: Denmark | Statement: [Nielsen, hasRegionOfPrevalence, Denmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denmark
Context triple: [Nielsen, hasRegionOfPrevalence, Denmark]
  • A. Denmark chosen
    Denmark is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and role as a founding member of NATO and the United Nations.
  • B. Norway
    Norway is a Nordic country in Northern Europe known for its high standard of living, extensive welfare state, and dramatic natural landscapes of fjords, mountains, and coastline.
  • C. Denmark–Norway
    Denmark–Norway was an early modern dual monarchy uniting the kingdoms of Denmark and Norway (including their overseas territories) under a single crown from the 16th to the early 19th century.
  • D. Sweden
    Sweden is a Nordic country in Northern Europe known for its high standard of living, strong welfare state, and long-standing policy of neutrality.
  • E. Finland
    Finland is a Nordic country in Northern Europe known for its extensive forests and lakes, high standard of living, strong welfare state, and history that includes fighting in World War II and maintaining a policy of military non-alignment during the Cold War.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasRegionOfPrevalence
Context triple: [Nielsen, hasRegionOfPrevalence, Denmark]
  • A. prevalentIn chosen
    Indicates that something occurs frequently or is commonly found within a particular context, group, or environment.
  • B. hasRegion
    Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
  • C. hasTypicalUsageRegion
    Indicates that something is most commonly or characteristically used within a particular geographic region.
  • D. usedInRegion
    Indicates that something is utilized or applied within a specific geographic or administrative region.
  • E. observedInRegion
    Indicates that something has been detected, recorded, or seen occurring within a specified geographic or spatial region.
  • F. None of above.

Provenance (4 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd568cf481908d10cf19a3ce28f3 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb2f3df34819090d942aad0a409fa completed March 7, 2026, 11:21 p.m.
PD Predicate disambiguation batch_69a4bb5bacc481909e8dfd5215e4711a completed March 1, 2026, 10:19 p.m.
Created at: March 1, 2026, 7:45 p.m.