Triple

T6173827
Position Surface form Disambiguated ID Type / Status
Subject Wannsee district E137768 entity
Predicate locatedOn P40 FINISHED
Object Wannsee lake E54046 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: Wannsee lake | Statement: [Wannsee district, locatedOn, Wannsee lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wannsee lake
Context triple: [Wannsee district, locatedOn, Wannsee lake]
  • A. Großer Wannsee lake chosen
    Großer Wannsee lake is a popular recreational lake in southwestern Berlin, known for its beaches, sailing, and proximity to historically significant sites.
  • B. Rothsee
    Rothsee is an artificial recreational lake in Middle Franconia, Bavaria, popular for swimming, sailing, and other water sports.
  • C. Weißer See
    Weißer See is a small urban lake and popular recreational spot located in Berlin's Weißensee district.
  • D. Grunewaldsee
    Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
  • E. Jungfernsee
    Jungfernsee is a scenic lake on the outskirts of Potsdam and Berlin, known for its historic villas, palaces, and location along the former inner 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_69c008a68c508190a8d78245c865960e completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c05d94c47481909745b2533926a1ca completed March 22, 2026, 9:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c141b200788190bd8d968edba53e5f completed March 23, 2026, 1:35 p.m.
Created at: March 22, 2026, 4:18 p.m.