Triple

T8723165
Position Surface form Disambiguated ID Type / Status
Subject Diocese of Helsingør E207061 entity
Predicate locatedIn 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: [Diocese of Helsingør, locatedIn, Zealand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zealand
Context triple: [Diocese of Helsingør, locatedIn, 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. Eteläsatama
    Eteläsatama is Helsinki’s central South Harbour, a key maritime hub and scenic waterfront area serving ferries, cruise ships, and seaside promenades near the city center.
  • 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_69ca835811d8819081ea00fd2a2c9a1c completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d0791208190b043332247372d7b completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf290001108190a90784b13a0a25b1 completed April 3, 2026, 2:42 a.m.
Created at: March 30, 2026, 6:36 p.m.