Triple

T2287244
Position Surface form Disambiguated ID Type / Status
Subject Bad Kleinen E51420 entity
Predicate hasNearbyCity P350 FINISHED
Object Schwerin E138060 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: Schwerin | Statement: [Bad Kleinen, hasNearbyCity, Schwerin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schwerin
Context triple: [Bad Kleinen, hasNearbyCity, Schwerin]
  • A. Schwerin chosen
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • B. Neubrandenburg
    Neubrandenburg is a historic city in northeastern Germany known for its well-preserved medieval brick Gothic architecture and distinctive city wall with multiple gate towers.
  • C. 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.
  • D. Wismar
    Wismar is a historic Hanseatic port city on Germany’s Baltic Sea coast, known for its well-preserved medieval architecture and UNESCO-listed old town.
  • E. Rostock
    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.
  • 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_69a88b09c644819090b503456d96bf70 completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc24868048190940512fd6449d99e completed March 7, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe87925a48190a7a5bd65d9a24c8b completed March 10, 2026, 9:46 a.m.
Created at: March 4, 2026, 7:48 p.m.