Triple

T13110521
Position Surface form Disambiguated ID Type / Status
Subject Greiz E310957 entity
Predicate locatedNear P294 FINISHED
Object Zwickau E102035 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: Zwickau | Statement: [Greiz, locatedNear, Zwickau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zwickau
Context triple: [Greiz, locatedNear, Zwickau]
  • A. Zwickau chosen
    Zwickau is a city in the German state of Saxony known historically as an important center of the automotive industry and as the birthplace of composer Robert Schumann.
  • B. Chemnitz
    Chemnitz is a city in eastern Germany known for its industrial heritage and post-reunification urban redevelopment.
  • C. 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.
  • D. Crimmitschau
    Crimmitschau is a town in the German state of Saxony, historically known for its textile industry and located within the broader Leipzig metropolitan area.
  • E. Liebenwalde
    Liebenwalde is a small town and municipality in the Oberhavel district of the German state of Brandenburg.
  • 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_69d806a872d08190a329806f8ff30df4 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9817e4f408190b77c198b4157d77a completed April 10, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fec869957481909ea4fded01851b70 completed May 9, 2026, 5:38 a.m.
Created at: April 9, 2026, 9:05 p.m.