Triple

T12158239
Position Surface form Disambiguated ID Type / Status
Subject Wurzen E289633 entity
Predicate connectedByRailTo P848 FINISHED
Object Döbeln E447957 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: Döbeln | Statement: [Wurzen, connectedByRailTo, Döbeln]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Döbeln
Context triple: [Wurzen, connectedByRailTo, Döbeln]
  • A. Döbeln chosen
    Döbeln is a small town in the German state of Saxony, known for its historic center and location between the cities of Leipzig, Dresden, and Chemnitz.
  • B. Schleiz
    Schleiz is a historic town in eastern Thuringia, Germany, known for its role as a former princely residence and for the nearby Schleizer Dreieck motor racing circuit.
  • C. Kronach
    Kronach is a historic town in northern Bavaria, Germany, known for its well-preserved medieval old town and the imposing Rosenberg Fortress.
  • D. Kulmbach
    Kulmbach is a historic Bavarian town in northern Germany renowned for its beer brewing tradition and its hilltop Plassenburg Castle.
  • E. Wurzen
    Wurzen is a historic town in the German state of Saxony, known for its medieval architecture and location on the river Mulde east of Leipzig.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915c277e481908351bf4e664dda42 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6eac128408190a29b4f8a6e1240dd completed May 3, 2026, 6:27 a.m.
Created at: April 8, 2026, 9:50 p.m.