Triple

T6320461
Position Surface form Disambiguated ID Type / Status
Subject Bezirk Magdeburg E141723 entity
Predicate contains P35 FINISHED
Object Salzwedel E385908 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: Salzwedel | Statement: [Bezirk Magdeburg, contains, Salzwedel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salzwedel
Context triple: [Bezirk Magdeburg, contains, Salzwedel]
  • A. Salzwedel chosen
    Salzwedel is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and as the birthplace of Jenny von Westphalen, the wife of Karl Marx.
  • B. 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.
  • C. 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.
  • D. Jüterbog
    Jüterbog is a historic town in the German state of Brandenburg, known for its medieval architecture and long-standing cultural heritage.
  • E. 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.
  • 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_69c008d13b8c8190be47d896eb735605 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c064c61f008190b316b9ff1023b057 completed March 22, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c66376b63081909fefd93790fa4b55 completed March 27, 2026, 11:01 a.m.
Created at: March 22, 2026, 4:29 p.m.