Triple

T7367574
Position Surface form Disambiguated ID Type / Status
Subject Treptow-Köpenick E169909 entity
Predicate hasLake P1025 FINISHED
Object Müggelsee E157949 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: Müggelsee | Statement: [Treptow-Köpenick, hasLake, Müggelsee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Müggelsee
Context triple: [Treptow-Köpenick, hasLake, Müggelsee]
  • A. Müggelsee chosen
    Müggelsee is the largest lake in Berlin, Germany, known for its popular recreational areas and natural surroundings.
  • B. Starnberger See
    Starnberger See is a large, scenic lake in southern Germany known for its affluent lakeside communities, recreational activities, and historical associations with Bavarian royalty.
  • 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. 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.
  • E. Grunewaldsee
    Grunewaldsee is a popular forest lake in Berlin known for its scenic surroundings and dog-friendly bathing areas.
  • 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_69c68a5ade988190885b7175f63b7534 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f17ea0608190955ac3474f6da7bb completed March 27, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69c802bc25908190ad444de63b7526a0 completed March 28, 2026, 4:33 p.m.
Created at: March 27, 2026, 3:06 p.m.