Triple

T7653046
Position Surface form Disambiguated ID Type / Status
Subject Wolfenbüttel E173302 entity
Predicate twinTown P1072 FINISHED
Object Blankenburg (Harz) E318587 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: Blankenburg (Harz) | Statement: [Wolfenbüttel, twinTown, Blankenburg (Harz)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Blankenburg (Harz)
Context triple: [Wolfenbüttel, twinTown, Blankenburg (Harz)]
  • A. Blankenburg (Harz) chosen
    Blankenburg (Harz) is a historic town in the Harz Mountains of central Germany, known for its medieval castle, scenic landscapes, and traditional architecture.
  • B. Herzberg am Harz
    Herzberg am Harz is a small town in Lower Saxony, Germany, located on the southern edge of the Harz Mountains and known for its historic castle and timber-framed architecture.
  • C. Benneckenstein (Harz)
    Benneckenstein (Harz) is a small town in the Harz Mountains of central Germany, now incorporated into the town of Oberharz am Brocken.
  • D. Bernlohe
    Bernlohe is a village-level district that forms part of the town of Roth in Bavaria, Germany.
  • E. Treuenbrietzen
    Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
  • 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_69c6995473348190a4f41d110d619a18 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018c34a88190be6089a9105bd4b0 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89af47b9c819087d42f1b01c413fe completed March 29, 2026, 3:22 a.m.
Created at: March 27, 2026, 3:59 p.m.