Triple

T4652755
Position Surface form Disambiguated ID Type / Status
Subject Kežmarok E102333 entity
Predicate hasTwinTown P919 FINISHED
Object Waren (Müritz)
Waren (Müritz) is a town in the Mecklenburg Lake District of northeastern Germany, known as a gateway to the Müritz National Park and a popular lakeside tourist destination.
 E457981 NE FINISHED

How this triple was built (4 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: Waren (Müritz) | Statement: [Kežmarok, hasTwinTown, Waren (Müritz)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Waren (Müritz)
Context triple: [Kežmarok, hasTwinTown, Waren (Müritz)]
  • A. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • B. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • C. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • D. Friedrichsruh
    Friedrichsruh is a small village in northern Germany best known as the estate and final residence of statesman Otto von Bismarck.
  • E. Birkenwerder
    Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Waren (Müritz)
Triple: [Kežmarok, hasTwinTown, Waren (Müritz)]
Generated description
Waren (Müritz) is a town in the Mecklenburg Lake District of northeastern Germany, known as a gateway to the Müritz National Park and a popular lakeside tourist destination.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Waren (Müritz)
Target entity description: Waren (Müritz) is a town in the Mecklenburg Lake District of northeastern Germany, known as a gateway to the Müritz National Park and a popular lakeside tourist destination.
  • A. Heringsdorf
    Heringsdorf is a seaside resort town on the Baltic Sea coast of the island of Usedom in northeastern Germany, known for its historic pier and spa architecture.
  • B. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • C. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • D. Friedrichsruh
    Friedrichsruh is a small village in northern Germany best known as the estate and final residence of statesman Otto von Bismarck.
  • E. Birkenwerder
    Birkenwerder is a small municipality in the German state of Brandenburg, located just north of Berlin and known for its residential character and surrounding forests.
  • F. None of above. chosen

Provenance (5 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_69bd43d71a308190afea7280841b0de8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6314883481908f085a7af497b0d8 completed March 20, 2026, 3:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaeb1ee081909ef641953bdf8df3 completed March 21, 2026, 1:56 a.m.
NEDg Description generation batch_69bdfbc12acc8190b8116a6003abb3e3 completed March 21, 2026, 2 a.m.
NED2 Entity disambiguation (via description) batch_69bdfc44536c8190a71e52b0690a7570 completed March 21, 2026, 2:02 a.m.
Created at: March 20, 2026, 1:14 p.m.