Triple

T5371392
Position Surface form Disambiguated ID Type / Status
Subject North Hesse E108856 entity
Predicate hasTourismAttraction P5121 FINISHED
Object Edersee E269254 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: Edersee | Statement: [North Hesse, hasTourismAttraction, Edersee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edersee
Context triple: [North Hesse, hasTourismAttraction, Edersee]
  • A. Edersee chosen
    Edersee is a large artificial reservoir in northern Hesse, Germany, created by the Eder Dam and known for recreation, water sports, and its scenic surroundings.
  • B. Möhnesee
    Möhnesee is a municipality in North Rhine-Westphalia, Germany, known for its large reservoir and scenic recreational area around the Möhne River.
  • C. Würmsee
    Würmsee is the historical name of the Bavarian lake now known as Starnberger See, one of Germany’s largest and most famous lakes near Munich.
  • D. Salzgittersee
    Salzgittersee is a large recreational lake in the city of Salzgitter, Germany, popular for swimming, water sports, and leisure activities.
  • E. Dämeritzsee
    Dämeritzsee is a lake on the southeastern edge of Berlin, Germany, known as a popular recreational area and a key junction in the region’s interconnected waterways.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd86aa0f5c8190ba96554e75696f8e completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf3a94acc48190a4c0ea39c6b8a405 completed March 22, 2026, 12:40 a.m.
Created at: March 20, 2026, 2:02 p.m.