Triple

T6663198
Position Surface form Disambiguated ID Type / Status
Subject Ballerup E151526 entity
Predicate locatedNear P294 FINISHED
Object Copenhagen E12606 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: Copenhagen | Statement: [Ballerup, locatedNear, Copenhagen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Copenhagen
Context triple: [Ballerup, locatedNear, Copenhagen]
  • 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. Odense
    Odense is a historic Danish city on the island of Funen, best known as the birthplace of fairy-tale author Hans Christian Andersen and a cultural hub with museums, festivals, and a vibrant literary heritage.
  • C. Aarhus
    Aarhus is Denmark’s second-largest city, a major cultural and economic center on the Jutland peninsula known for its universities, vibrant arts scene, and historic harbor.
  • D. Copenhagen metropolitan area
    The Copenhagen metropolitan area is the densely populated urban region centered on Denmark’s capital city, encompassing its surrounding suburbs and commuter towns.
  • E. Esbjerg
    Esbjerg is a major Danish port city on the North Sea, known for its offshore oil and wind industry, maritime heritage, and role as a regional economic center in western Jutland.
  • 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_69c687f5fac48190a09e4838d9c6b45d completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b09a6fa88190ba8e454b9ad421a0 completed March 27, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6eed99a1c8190b37da0ffed24e203 completed March 27, 2026, 8:55 p.m.
Created at: March 27, 2026, 2:02 p.m.