Triple

T13413514
Position Surface form Disambiguated ID Type / Status
Subject Kettwiger See E320149 entity
Predicate locatedDownstreamOf P5956 FINISHED
Object Baldeneysee E317107 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: Baldeneysee | Statement: [Kettwiger See, locatedDownstreamOf, Baldeneysee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baldeneysee
Context triple: [Kettwiger See, locatedDownstreamOf, Baldeneysee]
  • A. Baldeneysee chosen
    Baldeneysee is a large artificial lake and popular recreational area on the Ruhr River in Essen, Germany, known for sailing, rowing, and lakeside leisure activities.
  • B. Braassemermeer
    Braassemermeer is a lake in the Dutch province of South Holland, known for recreational boating and water sports.
  • C. Kloosterveen
    Kloosterveen is a residential district of the city of Assen in the province of Drenthe in the Netherlands.
  • D. Wendsee
    Wendsee is a lake in the German state of Brandenburg that forms part of the interconnected waterway system near Plauer See.
  • E. Münsterländer Bucht
    The Münsterländer Bucht is a lowland region in northwestern Germany characterized by fertile plains, agriculture, and the city of Münster as its main urban center.
  • 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaeb556948190af008c88e5bbf051 completed April 12, 2026, 2:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7307e9b5881908eb2cd9e4fa7c5f2 completed May 3, 2026, 11:24 a.m.
Created at: April 9, 2026, 9:35 p.m.