Triple

T6417633
Position Surface form Disambiguated ID Type / Status
Subject Hiddensee E127869 entity
Predicate partOf P40 FINISHED
Object Mecklenburg-Vorpommern E9737 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: Mecklenburg-Vorpommern | Statement: [Hiddensee, partOf, Mecklenburg-Vorpommern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mecklenburg-Vorpommern
Context triple: [Hiddensee, partOf, Mecklenburg-Vorpommern]
  • A. Mecklenburg-Vorpommern chosen
    Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
  • B. Schleswig-Holstein
    Schleswig-Holstein is Germany’s northernmost state, known for its North Sea and Baltic Sea coastlines, maritime heritage, and shared border with Denmark.
  • C. Brandenburg
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • D. Thuringia
    Thuringia is a federal state in central Germany known for its forested landscapes, historic cities like Weimar and Erfurt, and its rich cultural and intellectual heritage.
  • E. Saxony-Anhalt
    Saxony-Anhalt is a federal state in central Germany known for its rich cultural heritage, including numerous UNESCO World Heritage Sites such as the Bauhaus in Dessau and the historic towns of Quedlinburg and Wittenberg.
  • 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_69c0083815208190a9b299b8e0640218 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c068ea06b08190901e0c0a18fd5170 completed March 22, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c6ec470819088f16fd762d3c7d7 completed March 28, 2026, 9:16 a.m.
Created at: March 22, 2026, 4:42 p.m.