Triple

T7059744
Position Surface form Disambiguated ID Type / Status
Subject Köpenick E164184 entity
Predicate partOf P40 FINISHED
Object Treptow-Köpenick borough 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: Treptow-Köpenick borough | Statement: [Köpenick, partOf, Treptow-Köpenick borough]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Treptow-Köpenick borough
Context triple: [Köpenick, partOf, Treptow-Köpenick borough]
  • 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. Friedrichswerder district
    Friedrichswerder district is a historic quarter in central Berlin, Germany, known for its 19th-century architecture and cultural landmarks.
  • D. 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.
  • E. Tempelhof-Schöneberg
    Tempelhof-Schöneberg is a borough of Berlin, Germany, known for its mix of historic residential areas, the former Tempelhof Airport, and significant Cold War-era political sites.
  • 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_69c688796c148190adb2f1596f595f22 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e458ad9c81908c3f492b317ce291 completed March 27, 2026, 8:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83423e5008190881a7e956c716687 completed March 28, 2026, 8:03 p.m.
Created at: March 27, 2026, 2:38 p.m.