Triple

T6495882
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Neubrandenburg E148157 entity
Predicate notableCity P2813 FINISHED
Object Waren (Müritz) E457981 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: Waren (Müritz) | Statement: [Bezirk Neubrandenburg, notableCity, Waren (Müritz)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waren (Müritz)
Context triple: [Bezirk Neubrandenburg, notableCity, Waren (Müritz)]
  • A. Waren (Müritz) chosen
    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.
  • B. 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.
  • C. Ueckermünde
    Ueckermünde is a small historic port town in northeastern Germany on the Szczecin Lagoon, known for its maritime heritage and access to the Baltic Sea.
  • D. Hasselwerder
    Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
  • E. Maienwerder
    Maienwerder is a small island located in the Tegeler See lake in Berlin, Germany, known for its natural setting and limited accessibility.
  • 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_69c009088f3081909cd467b05919de30 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06ab958808190bd85e007e925ffc4 completed March 22, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653c414f08190be64a337fc936a6f completed March 27, 2026, 9:54 a.m.
Created at: March 22, 2026, 4:53 p.m.