Triple

T1431748
Position Surface form Disambiguated ID Type / Status
Subject Gunnar E30461 entity
Predicate hasUsageRegion P908 FINISHED
Object Denmark E5474 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: Denmark | Statement: [Gunnar, hasUsageRegion, Denmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Denmark
Context triple: [Gunnar, hasUsageRegion, 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.

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_69a498fc69ec8190b61722bd4b67c4d2 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c4ddbe208190a68cb000a6970d17 completed March 1, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad014e33488190b50469c727b32639 completed March 8, 2026, 4:55 a.m.
Created at: March 1, 2026, 8 p.m.