Triple

T14644570
Position Surface form Disambiguated ID Type / Status
Subject Mecklenburgische Schweiz E343812 entity
Predicate hasSettlement P1068 FINISHED
Object Teterow E580917 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: Teterow | Statement: [Mecklenburgische Schweiz, hasSettlement, Teterow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teterow
Context triple: [Mecklenburgische Schweiz, hasSettlement, Teterow]
  • A. Teterow chosen
    Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
  • B. Jastorf
    Jastorf is a village in northern Germany best known as the namesake and key archaeological site of the early Iron Age Jastorf culture.
  • C. Retzow
    Retzow is a small municipality in the Havelland district of the federal state of Brandenburg in northeastern Germany.
  • D. Wandlitz
    Wandlitz is a municipality in the German state of Brandenburg, known for its lakes, forests, and proximity to Berlin.
  • E. Schwedt
    Schwedt is a town in northeastern Germany, located on the Oder River near the Polish border, known for its industrial facilities and cross-border regional ties.
  • 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_69ff6ec12de8819097cd83530e54f54b completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 1:26 a.m.