Triple

T18309305
Position Surface form Disambiguated ID Type / Status
Subject Prince Vincent of Denmark E438576 entity
Predicate birthPlace P1 FINISHED
Object Copenhagen, Denmark 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: Copenhagen, Denmark | Statement: [Prince Vincent of Denmark, birthPlace, Copenhagen, Denmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copenhagen, Denmark
Context triple: [Prince Vincent of Denmark, birthPlace, Copenhagen, Denmark]
  • A. Copenhagen chosen
    Copenhagen is the capital and largest city of Denmark, known for its historic architecture, vibrant cultural scene, and high quality of life.
  • B. Copenhagen
    Copenhagen is a popular American smokeless tobacco (chewing tobacco/dip) brand known for its long history and strong presence in the U.S. market.
  • C. 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.
  • D. UN City Copenhagen
    UN City Copenhagen is a modern, sustainable office complex in Denmark that serves as the Nordic headquarters for multiple United Nations agencies.
  • E. Bergen, Denmark
    Bergen, Denmark is a small Danish town known for its rural character and cultural ties to its German twin town, Bergen.
  • 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_69d8b915e3e881909125d760c15d0c29 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e5021709f88190a8047dd57edc2029 completed April 19, 2026, 4:25 p.m.
Created at: April 10, 2026, 10:36 a.m.