Triple

T8592339
Position Surface form Disambiguated ID Type / Status
Subject RKP E203458 entity
Predicate traditionalStronghold P46972 FINISHED
Object Åboland E210759 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: Åboland | Statement: [RKP, traditionalStronghold, Åboland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åboland
Context triple: [RKP, traditionalStronghold, Åboland]
  • A. Åboland chosen
    Åboland is a Swedish-speaking coastal and archipelago region in southwestern Finland known for its strong cultural and linguistic ties to the Swedish minority.
  • B. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • C. 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.
  • D. Schwedeninsel
    Schwedeninsel is a small, wooded island located in the Bavarian lake Ammersee in southern Germany.
  • E. Jylland
    Jylland is a historical region in Denmark located on the Jutland Peninsula, known for its rural landscapes, coastal areas, and cultural heritage.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc5c2d852081908901f5d2a47035b0 completed March 31, 2026, 11:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8b584088190bc5b8b2785894d82 completed April 2, 2026, 5:34 p.m.
Created at: March 30, 2026, 6:23 p.m.