Triple

T6473839
Position Surface form Disambiguated ID Type / Status
Subject Kalundborg E146019 entity
Predicate partOf P40 FINISHED
Object Region Zealand E215864 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: Region Zealand | Statement: [Kalundborg, partOf, Region Zealand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Region Zealand
Context triple: [Kalundborg, partOf, Region Zealand]
  • A. Region Zealand chosen
    Region Zealand is an administrative region in eastern Denmark that encompasses the southern and western parts of the island of Zealand and nearby islands.
  • B. Zealand
    Zealand is the largest and most populous island of Denmark, home to the capital city Copenhagen and a central hub of the country’s cultural and economic life.
  • C. Zealand Region
    Zealand Region is an administrative region of Denmark that encompasses the island of Zealand (excluding the Copenhagen area) and nearby islands, with responsibilities for healthcare and regional development.
  • D. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • E. Seeland region
    The Seeland region is an area in western Switzerland known for its lakes, fertile plains, and intensive agriculture, particularly vegetable farming.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a32c0188190bcb3c35fc1d796a6 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c65fd1db288190b00ba6d7f3aae925 completed March 27, 2026, 10:45 a.m.
Created at: March 22, 2026, 4:50 p.m.