Triple

T7488481
Position Surface form Disambiguated ID Type / Status
Subject South Jutland E176942 entity
Predicate historicalName P65 FINISHED
Object Sønderjylland E246174 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: Sønderjylland | Statement: [South Jutland, historicalName, Sønderjylland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sønderjylland
Context triple: [South Jutland, historicalName, Sønderjylland]
  • A. Schleswig chosen
    Schleswig is a historic town in northern Germany known for its Viking heritage, medieval cathedral, and location on the Schlei inlet.
  • B. Lolland
    Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
  • C. Jylland
    Jylland is a historical region in Denmark located on the Jutland Peninsula, known for its rural landscapes, coastal areas, and cultural heritage.
  • D. Funen
    Funen is Denmark’s third-largest island, located between the Jutland Peninsula and Zealand and known for its rolling countryside and the city of Odense, birthplace of Hans Christian Andersen.
  • E. Djursland
    Djursland is a rural peninsula in eastern Jutland, Denmark, known for its varied coastline, beaches, and popular holiday and nature tourism.
  • 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_69c69f24ac508190bb98fe927c0bd065 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f55965ac81909d3c3a5422b22d44 completed March 27, 2026, 9:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84eed875c81908922057730834a84 completed March 28, 2026, 9:58 p.m.
Created at: March 27, 2026, 3:43 p.m.