Triple

T6848229
Position Surface form Disambiguated ID Type / Status
Subject Müggelsee E157949 entity
Predicate locatedIn P40 FINISHED
Object Berlin-Köpenick E169909 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: Berlin-Köpenick | Statement: [Müggelsee, locatedIn, Berlin-Köpenick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berlin-Köpenick
Context triple: [Müggelsee, locatedIn, Berlin-Köpenick]
  • A. Treptow-Köpenick chosen
    Treptow-Köpenick is Berlin’s largest and greenest borough, known for its extensive forests, lakes, and historic town centers such as Köpenick.
  • B. Pankow
    Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
  • C. Reinickendorf
    Reinickendorf is a borough in the northwest of Berlin, Germany, known for its mix of residential neighborhoods, industrial areas, and green spaces including parts of Lake Tegel.
  • D. Steglitz-Zehlendorf
    Steglitz-Zehlendorf is a borough in southwestern Berlin known for its affluent residential areas, lakes and forests, and historically significant sites such as the Wannsee Conference villa.
  • E. Berlin-Lichtenberg
    Berlin-Lichtenberg is a borough in eastern Berlin known for its mix of post-war residential areas, historical sites, and former East German administrative and security institutions.
  • 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_69c6882ed4c081909dc465a7cf8838be completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d7ce3e7481908e0472b8faafa473 completed March 27, 2026, 7:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7a309dd4c81909f2a652f211911bc completed March 28, 2026, 9:44 a.m.
Created at: March 27, 2026, 2:20 p.m.