Triple

T2805378
Position Surface form Disambiguated ID Type / Status
Subject University of Copenhagen E54039 entity
Predicate region P40 FINISHED
Object Zealand E38167 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: Zealand | Statement: [University of Copenhagen, region, Zealand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zealand
Context triple: [University of Copenhagen, region, Zealand]
  • A. Zealand chosen
    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.
  • B. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • C. Schwedeninsel
    Schwedeninsel is a small, wooded island located in the Bavarian lake Ammersee in southern Germany.
  • D. Åboland
    Åboland is a Swedish-speaking coastal and archipelago region in southwestern Finland known for its strong cultural and linguistic ties to the Swedish minority.
  • E. Zuidland
    Zuidland is a village in the western Netherlands, located in the province of South Holland.
  • 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_69ab49dcee188190b5c6eca9ae9e3469 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde1525888190b3c04e10043c67d6 completed March 7, 2026, 8:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69afc674217c81908177b088cc824e7b completed March 10, 2026, 7:21 a.m.
Created at: March 6, 2026, 9:59 p.m.