Triple

T12749650
Position Surface form Disambiguated ID Type / Status
Subject Hanse Sail E304695 entity
Predicate organisedBy P123 FINISHED
Object City of Rostock E56817 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: City of Rostock | Statement: [Hanse Sail, organisedBy, City of Rostock]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Rostock
Context triple: [Hanse Sail, organisedBy, City of Rostock]
  • A. Rostock chosen
    Rostock is a historic Hanseatic city in northern Germany known for its significant seaport on the Baltic Sea and its long maritime and trading tradition.
  • B. Lübeck
    Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • C. Stralsund
    Stralsund is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval old town and brick Gothic architecture.
  • D. Luisenstadt
    Luisenstadt is a historic former district of Berlin, Germany, known for its 19th-century urban development and significant cultural and architectural heritage.
  • E. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • 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_69d7bdf1fcd081909ffb0e0d6fa3a07d completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96bd75f508190aaae0969f33d1523 completed April 10, 2026, 9:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6a54061dc8190849855f035d63300 completed May 3, 2026, 1:30 a.m.
Created at: April 9, 2026, 5:27 p.m.