Triple

T8442575
Position Surface form Disambiguated ID Type / Status
Subject Wuhlheide E199582 entity
Predicate locatedNear P294 FINISHED
Object Köpenick E164184 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: Köpenick | Statement: [Wuhlheide, locatedNear, Köpenick]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Köpenick
Context triple: [Wuhlheide, locatedNear, Köpenick]
  • A. Köpenick chosen
    Köpenick is a historic, green district in southeastern Berlin known for its old town, baroque palace on the Dahme River, and extensive forests and lakes.
  • B. Zossen
    Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after World War II.
  • C. Teterow
    Teterow is a small historic town in northeastern Germany known for its medieval architecture and location in the Mecklenburg Lake District.
  • D. Pankow
    Pankow is a northeastern borough of Berlin known for its mix of historic neighborhoods, green spaces, and the popular district of Prenzlauer Berg.
  • E. Brandenburg an der Havel
    Brandenburg an der Havel is a historic town in eastern Germany, considered one of the cradles of the state of Brandenburg and known for its medieval architecture and waterways.
  • 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_69ca83170f9081909cd98f55614c6476 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe310d8e08190b871bda79acde678 completed March 31, 2026, 3:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4dc163488190a53d8696fdba94b5 completed April 2, 2026, 11:06 a.m.
Created at: March 30, 2026, 6:08 p.m.