Triple

T16540151
Position Surface form Disambiguated ID Type / Status
Subject Karl Asmund Rudolphi E401798 entity
Predicate workLocation P7 FINISHED
Object Greifswald E159331 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: Greifswald | Statement: [Karl Asmund Rudolphi, workLocation, Greifswald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greifswald
Context triple: [Karl Asmund Rudolphi, workLocation, 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 (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_69d88384bc30819084229e7dcdc39a41 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3455bd43c8190b01560d4af55a9e0 completed April 18, 2026, 8:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a006ed9fa988190892ca20939080f5f completed May 10, 2026, 11:41 a.m.
Created at: April 10, 2026, 5:15 a.m.