Triple

T13826152
Position Surface form Disambiguated ID Type / Status
Subject Principality of Reuss Younger Line E332253 entity
Predicate capital P234 FINISHED
Object Schleiz E527783 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: Schleiz | Statement: [Principality of Reuss Younger Line, capital, Schleiz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schleiz
Context triple: [Principality of Reuss Younger Line, capital, Schleiz]
  • A. Schleiz chosen
    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.
  • B. Döbeln
    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.
  • 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. 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.
  • 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_69d81c5ae7c88190b0dd41bdafeb5999 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de0295d2d48190b08eba0d805bd72d completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f1f80648190a4a0e8260ac95194 completed May 9, 2026, 4:21 p.m.
Created at: April 9, 2026, 10:13 p.m.