Triple

T19656703
Position Surface form Disambiguated ID Type / Status
Subject University of Greifswald E471966 entity
Predicate locatedIn P40 FINISHED
Object Greifswald NE NERFINISHED

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: Greifswald | Statement: [University of Greifswald, locatedIn, Greifswald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greifswald
Context triple: [University of Greifswald, locatedIn, Greifswald]
  • A. Greifswald chosen
    Greifswald is a historic Hanseatic university city in northeastern Germany, located near the Baltic Sea.
  • B. 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.
  • C. Ratzeburg
    Ratzeburg is a historic town in northern Germany known for its island old town and Romanesque cathedral, situated in the lake district of Schleswig-Holstein.
  • D. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e51395348190ac1416d46dfc6db0 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e64146539c8190813debb0d964bc23 completed April 20, 2026, 3:07 p.m.
Created at: April 10, 2026, 1:45 p.m.