Triple

T20895151
Position Surface form Disambiguated ID Type / Status
Subject Tegeler Hafen E514512 entity
Predicate hasWaterBody P165 FINISHED
Object Tegeler See NE NERFINISHED

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: Tegeler See | Statement: [Tegeler Hafen, hasWaterBody, Tegeler See]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegeler See
Context triple: [Tegeler Hafen, hasWaterBody, Tegeler See]
  • A. Tegeler See chosen
    Tegeler See is a large lake in the Tegel district of Berlin, Germany, popular for recreation, boating, and its surrounding natural areas.
  • B. Schlachtensee
    Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
  • C. Griebnitzsee
    Griebnitzsee is a lake on the southwestern outskirts of Berlin, Germany, known for its scenic waterfront, historic villas, and role as part of the former inner German border.
  • D. Wandlitzsee
    Wandlitzsee is a scenic lake in Brandenburg, Germany, known for recreation, bathing, and its proximity to the village of Wandlitz.
  • E. Ratzeburger See
    Ratzeburger See is a large glacial lake in northern Germany known for its scenic surroundings and the town of Ratzeburg situated on an island within it.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4f7ebe48190952a85547a0f31a1 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6d06129788190b88ab807af4641c1 completed April 21, 2026, 1:18 a.m.
Created at: April 16, 2026, 12:47 p.m.