Triple

T7212494
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Schwerin E149439 entity
Predicate locatedIn P40 FINISHED
Object Mecklenburg region E9737 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: Mecklenburg region | Statement: [Bezirk Schwerin, locatedIn, Mecklenburg region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mecklenburg region
Context triple: [Bezirk Schwerin, locatedIn, Mecklenburg region]
  • A. Mecklenburg-Vorpommern chosen
    Mecklenburg-Vorpommern is a federal state in northeastern Germany known for its Baltic Sea coastline, numerous lakes, and relatively low population density.
  • B. Mecklenburgische Seenplatte district
    The Mecklenburgische Seenplatte district is a large rural district in the German state of Mecklenburg-Vorpommern, renowned for its extensive lake district and natural landscapes.
  • C. Nordwestmecklenburg
    Nordwestmecklenburg is a rural district in the German state of Mecklenburg-Vorpommern, known for its Baltic Sea coastline and historic towns.
  • D. Lower Saxony
    Lower Saxony is a large federal state in northwestern Germany known for its diverse landscapes, strong industrial base, and historic cities such as Hanover and Göttingen.
  • E. Brandenburg
    Brandenburg is a federal state in northeastern Germany that surrounds Berlin and is known for its lakes, forests, and historic Prussian heritage.
  • 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_69c687eca814819095abb52316b1af80 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6e98b61448190add3624a818fdc7b completed March 27, 2026, 8:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8682696a48190aec021bd00c6f633 completed March 28, 2026, 11:45 p.m.
Created at: March 27, 2026, 2:53 p.m.