Triple

T9005059
Position Surface form Disambiguated ID Type / Status
Subject Fraueninsel E215121 entity
Predicate nearbyIsland P2064 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: [Fraueninsel, nearbyIsland, Krautinsel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Krautinsel
Context triple: [Fraueninsel, nearbyIsland, 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_69ca83a12d648190b1e4fe11e8a31890 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc695afa34819086cf6fcce2997b5f completed April 1, 2026, 12:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd0e3f0c88190ae688632be25e5c9 completed April 3, 2026, 2:38 p.m.
Created at: March 30, 2026, 7:05 p.m.