Triple

T696769
Position Surface form Disambiguated ID Type / Status
Subject Steglitz-Zehlendorf E13910 entity
Predicate contains P35 FINISHED
Object Schlachtensee lake E86005 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: Schlachtensee lake | Statement: [Steglitz-Zehlendorf, contains, Schlachtensee lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schlachtensee lake
Context triple: [Steglitz-Zehlendorf, contains, Schlachtensee lake]
  • A. Schlachtensee chosen
    Schlachtensee is a lake and popular recreational area in southwestern Berlin, known for swimming, walking trails, and its surrounding forested landscape.
  • B. Tegeler See
    Tegeler See is a large lake in the Tegel district of Berlin, Germany, popular for recreation, boating, and its surrounding natural areas.
  • C. Großer Wannsee lake
    Großer Wannsee lake is a popular recreational lake in southwestern Berlin, known for its beaches, sailing, and proximity to historically significant sites.
  • D. Heiligensee
    Heiligensee is a residential and partly lakeside locality in the northwest of Berlin, known for its green spaces and village-like character within the borough of Reinickendorf.
  • E. 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.
  • 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_69a493406c408190957eeec9048a8fb6 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4a0c8055881909565ebde2be8fd7a completed March 1, 2026, 8:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69a64a5618348190b8ec2c7d6bd06e2b completed March 3, 2026, 2:41 a.m.
Created at: March 1, 2026, 7:36 p.m.