Triple

T3230880
Position Surface form Disambiguated ID Type / Status
Subject Uckermark E67735 entity
Predicate largestTown P235 FINISHED
Object Prenzlau E163379 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: Prenzlau | Statement: [Uckermark, largestTown, Prenzlau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prenzlau
Context triple: [Uckermark, largestTown, Prenzlau]
  • A. Prenzlau chosen
    Prenzlau is a historic town in northeastern Germany’s Brandenburg region, known for its medieval architecture and role as a regional administrative center.
  • B. Fürstenwalde
    Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
  • C. Riesa
    Riesa is a town in the German state of Saxony, situated on the Elbe River and known historically as an important regional railway and industrial center.
  • D. Genthin
    Genthin is a small town in the German state of Saxony-Anhalt, historically part of Prussia and known for its location along the Elbe–Havel Canal.
  • E. Zinnowitz
    Zinnowitz is a seaside resort town on Germany’s Baltic Sea coast, known for its sandy beaches, historic spa architecture, and tourism on the island of Usedom.
  • 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_69ad858c61888190a31196310d9b30b5 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaeb99e088190a8eeca2ca53707e7 completed March 8, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd6786a558819098973b8f10b7e7cb completed March 20, 2026, 3:28 p.m.
Created at: March 8, 2026, 3:08 p.m.