Triple

T14644569
Position Surface form Disambiguated ID Type / Status
Subject Mecklenburgische Schweiz E343812 entity
Predicate near P350 FINISHED
Object Neubrandenburg E170908 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: Neubrandenburg | Statement: [Mecklenburgische Schweiz, near, Neubrandenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neubrandenburg
Context triple: [Mecklenburgische Schweiz, near, Neubrandenburg]
  • A. Neubrandenburg chosen
    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.
  • B. Pasewalk
    Pasewalk is a small historic town in northeastern Germany, located in the state of Mecklenburg-Vorpommern near the Polish border.
  • C. Schwerin
    Schwerin is a historic city in northern Germany known for its picturesque lakeside setting and landmark Schwerin Castle.
  • D. 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.
  • 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb4ea6d8481908e6331ca173c646b completed April 14, 2026, 9:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff01d44044819088c86f46b02404ed completed May 9, 2026, 9:43 a.m.
Created at: April 10, 2026, 1:26 a.m.