Triple

T17935513
Position Surface form Disambiguated ID Type / Status
Subject Jablonec nad Nisou E448452 entity
Predicate twinTown P1072 FINISHED
Object Bautzen NE NERFINISHED

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: Bautzen | Statement: [Jablonec nad Nisou, twinTown, Bautzen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bautzen
Context triple: [Jablonec nad Nisou, twinTown, Bautzen]
  • A. Bautzen chosen
    Bautzen is a historic town in eastern Germany known for its well-preserved medieval architecture and as a cultural center of the Sorbian minority.
  • B. Zittau
    Zittau is a historic town in the southeastern corner of Germany, known for its proximity to both the Czech and Polish borders and its well-preserved medieval architecture.
  • C. Liebenwalde
    Liebenwalde is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • D. Zschopau
    Zschopau is a historic town in Saxony, Germany, known for its location in the Ore Mountains and its long tradition of motorcycle manufacturing.
  • E. Görlitz
    Görlitz is a historic city in eastern Germany on the Lusatian Neisse River, known for its well-preserved old town and role as a popular film location.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f79d14819095540856928f0e25 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a55536e0819083dcfc4be71d447a completed April 19, 2026, 9:50 a.m.
Created at: April 10, 2026, 10:21 a.m.