Triple

T20459152
Position Surface form Disambiguated ID Type / Status
Subject Mark Brandenburg E501876 entity
Predicate contains P35 FINISHED
Object Teltow 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: Teltow | Statement: [Mark Brandenburg, contains, Teltow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teltow
Context triple: [Mark Brandenburg, contains, Teltow]
  • A. Teltow chosen
    Teltow is a town in the German state of Brandenburg, located just southwest of Berlin and known for its historical core and proximity to the capital.
  • B. Prignitz
    Prignitz is a rural district in northwestern Brandenburg, Germany, known for its historic towns, agricultural landscapes, and location along the Elbe River.
  • C. Groß Glienicke
    Groß Glienicke is a village and former border locality in the Berlin–Brandenburg area, known for its lakeside setting and historical division between East and West Germany.
  • D. Tornesch
    Tornesch is a small town in the district of Pinneberg in Schleswig-Holstein, northern Germany, known for its residential character and proximity to Hamburg.
  • E. Müritz
    Müritz is Germany’s largest lake entirely within the country, located in the Mecklenburg Lake District of northeastern Germany.
  • 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_69e0b4ad4940819098cf2ff6413574e5 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e696a4652c8190acf79fa2e285e436 completed April 20, 2026, 9:12 p.m.
Created at: April 16, 2026, 11:33 a.m.