Triple

T12968528
Position Surface form Disambiguated ID Type / Status
Subject Kamenz E321330 entity
Predicate hasTwinTown P919 FINISHED
Object Radeburg E1092144 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: Radeburg | Statement: [Kamenz, hasTwinTown, Radeburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Radeburg
Context triple: [Kamenz, hasTwinTown, Radeburg]
  • A. Radeburg chosen
    Radeburg is a small town in the German state of Saxony, situated north of Dresden and known for its historic center and surrounding rural landscape.
  • B. Radeberg
    Radeberg is a small town in the German state of Saxony, known for its Radeberger Pilsner brewery and historic town center near Dresden.
  • C. Tureberg
    Tureberg is a central district in Sollentuna Municipality, Sweden, known for housing the municipal center and key public services.
  • D. Treuenbrietzen
    Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
  • E. Löbau
    Löbau is a small town in the Free State of Saxony in eastern Germany, known for its historic architecture and location in the Lusatian Highlands.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e407e5081909424fc0c22483c28 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf0683b90819098864f73b6976517 completed May 8, 2026, 2:17 p.m.
Created at: April 9, 2026, 8:33 p.m.