Triple

T16214471
Position Surface form Disambiguated ID Type / Status
Subject Weißensee E393549 entity
Predicate namedAfter P63 FINISHED
Object Weißer See E445696 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: Weißer See | Statement: [Weißensee, namedAfter, Weißer See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Weißer See
Context triple: [Weißensee, namedAfter, Weißer See]
  • A. Weißer See chosen
    Weißer See is a small urban lake and popular recreational spot located in Berlin's Weißensee district.
  • B. Oberer See
    Oberer See is a small lake located in the town of Böblingen in the German state of Baden-Württemberg, used primarily for recreation and local leisure activities.
  • C. Svityaz Lake
    Svityaz Lake is the deepest and one of the largest natural lakes in Ukraine, renowned for its clear waters and location within the Shatsk National Nature Park.
  • D. Roś Lake
    Roś Lake is a scenic freshwater lake in northeastern Poland, known as part of the Masurian Lake District’s popular network of recreational and natural waterways.
  • E. Černé jezero
    Černé jezero is the largest and deepest glacial lake in the Czech Republic, located in the Šumava Mountains near the German border.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227f393e08190be93400d754f0a2d completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f87bd588190afb91d21eebd00e3 completed May 10, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:03 a.m.