Triple

T13312439
Position Surface form Disambiguated ID Type / Status
Subject Witten E317101 entity
Predicate hasTwinTown P919 FINISHED
Object Bitterfeld-Wolfen E118183 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: Bitterfeld-Wolfen | Statement: [Witten, hasTwinTown, Bitterfeld-Wolfen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bitterfeld-Wolfen
Context triple: [Witten, hasTwinTown, Bitterfeld-Wolfen]
  • A. Bitterfeld-Wolfen chosen
    Bitterfeld-Wolfen is a town in Saxony-Anhalt, Germany, known for its industrial heritage, particularly in chemical production and film manufacturing.
  • B. Oschersleben
    Oschersleben is a town in the German state of Saxony-Anhalt, known for its motorsport race track Motorsport Arena Oschersleben.
  • C. Dennewitz
    Dennewitz is a village in Brandenburg, Germany, historically notable as the site of a major 1813 battle during the Napoleonic Wars.
  • D. Haldensleben
    Haldensleben is a town in the German state of Saxony-Anhalt, known as an administrative and economic center with historical roots dating back to the Middle Ages.
  • E. Zerbst
    Zerbst is a historic town in Saxony-Anhalt, Germany, known as the birthplace of Catherine the Great and for its former role as a princely residence.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990f6d34c8190ba19dc2df7d42c22 completed April 11, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716e7b9a48190a33b04df8ad45ed8 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:29 p.m.