Triple

T15046024
Position Surface form Disambiguated ID Type / Status
Subject Staaken E379226 entity
Predicate adjacentTo P224 FINISHED
Object Falkensee E694697 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: Falkensee | Statement: [Staaken, adjacentTo, Falkensee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Falkensee
Context triple: [Staaken, adjacentTo, Falkensee]
  • A. Falkensee chosen
    Falkensee is a town in the Havelland district of Brandenburg, Germany, situated just west of Berlin and functioning largely as a residential suburb of the capital.
  • B. Grevesmühlen
    Grevesmühlen is a small town in the German state of Mecklenburg-Vorpommern, known as a local administrative and service center in the north of the country.
  • C. 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.
  • D. Stolzenhagen
    Stolzenhagen is a village and locality within the municipality of Wandlitz in the state of Brandenburg, Germany.
  • E. Rheinsberg
    Rheinsberg is a small historic town in Brandenburg, Germany, best known for its picturesque lakeside palace that served as a residence for Prussian 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded830c3c08190a87b81abbbb75377 completed April 15, 2026, 12:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69febfd954548190b3f7c60d95403f3e completed May 9, 2026, 5:02 a.m.
Created at: April 10, 2026, 3 a.m.