Triple

T8882899
Position Surface form Disambiguated ID Type / Status
Subject Herreninsel E211452 entity
Predicate hasNearbyIsland P970 FINISHED
Object Krautinsel E206839 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: Krautinsel | Statement: [Herreninsel, hasNearbyIsland, Krautinsel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krautinsel
Context triple: [Herreninsel, hasNearbyIsland, Krautinsel]
  • A. Krautinsel chosen
    Krautinsel is a small, uninhabited island in Germany’s Chiemsee lake, historically used for agriculture and known for its tranquil natural setting.
  • B. Sasseninsel
    Sasseninsel is a small island located in the Eibsee, a picturesque alpine lake near the Zugspitze in Bavaria, Germany.
  • C. Rübeland
    Rübeland is a village in the Harz Mountains of central Germany, known for its show caves and scenic natural surroundings.
  • D. Island of Usedom
    The Island of Usedom is a Baltic Sea island shared by Germany and Poland, renowned for its long sandy beaches, seaside resorts, and status as a popular holiday destination.
  • E. Ostland
    Ostland was a historical region in Eastern Europe that roughly encompassed the Baltic states and parts of western Belarus.
  • 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_69ca838f9e20819096ab1f236a70381a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc616a01f48190b8bbde0e898a38c7 completed April 1, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfabca74888190934593d6504fbed1 completed April 3, 2026, noon
Created at: March 30, 2026, 6:53 p.m.