Triple

T19003353
Position Surface form Disambiguated ID Type / Status
Subject Central Jutland E465011 entity
Predicate contains P35 FINISHED
Object Djursland NE NERFINISHED

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: Djursland | Statement: [Central Jutland, contains, Djursland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Djursland
Context triple: [Central Jutland, contains, Djursland]
  • A. Djursland chosen
    Djursland is a rural peninsula in eastern Jutland, Denmark, known for its varied coastline, beaches, and popular holiday and nature tourism.
  • B. Lolland
    Lolland is a large, predominantly agricultural island in southeastern Denmark known for its flat landscape and sugar beet production.
  • C. Fjerritslev
    Fjerritslev is a small Danish town in the North Jutland region, known historically for its agricultural surroundings and local brewery heritage.
  • D. Langeland
    Langeland is a Danish island in the South Funen Archipelago, known for its rural landscapes, coastal scenery, and historical villages.
  • E. Refshaleøen
    Refshaleøen is a former industrial island in Copenhagen, Denmark, now known for its creative hubs, cultural venues, and waterfront recreational spaces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6a252588190a40398b1879fb096 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.