Triple

T16799932
Position Surface form Disambiguated ID Type / Status
Subject Saxon Ore Mountain mining region E408328 entity
Predicate hasImportantTown P14082 FINISHED
Object Wolkenstein
Wolkenstein is a historic small town in the Ore Mountains of Saxony, Germany, known for its medieval castle, spa traditions, and long association with regional mining.
E1235163 NE FINISHED

How this triple was built (4 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: Wolkenstein | Statement: [Saxon Ore Mountain mining region, hasImportantTown, Wolkenstein]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolkenstein
Context triple: [Saxon Ore Mountain mining region, hasImportantTown, Wolkenstein]
  • A. Tettenweis
    Tettenweis is a small Bavarian village in Germany known as the birthplace of the Symbolist painter Franz von Stuck.
  • B. Gerswalde
    Gerswalde is a small rural municipality in the Uckermark district of Brandenburg, northeastern Germany.
  • C. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • D. Helmbrechts
    Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
  • E. Walhorn
    Walhorn is a village in the municipality of Lontzen in eastern Belgium, known for its rural character and historical setting near the German border.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Wolkenstein
Triple: [Saxon Ore Mountain mining region, hasImportantTown, Wolkenstein]
Generated description
Wolkenstein is a historic small town in the Ore Mountains of Saxony, Germany, known for its medieval castle, spa traditions, and long association with regional mining.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Wolkenstein
Target entity description: Wolkenstein is a historic small town in the Ore Mountains of Saxony, Germany, known for its medieval castle, spa traditions, and long association with regional mining.
  • A. Tettenweis
    Tettenweis is a small Bavarian village in Germany known as the birthplace of the Symbolist painter Franz von Stuck.
  • B. Gerswalde
    Gerswalde is a small rural municipality in the Uckermark district of Brandenburg, northeastern Germany.
  • C. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • D. Helmbrechts
    Helmbrechts is a small town in northern Bavaria, Germany, known for its textile industry and location in the Franconian Forest region.
  • E. Walhorn
    Walhorn is a village in the municipality of Lontzen in eastern Belgium, known for its rural character and historical setting near the German border.
  • F. None of above. chosen

Provenance (5 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2acd3548190a5f6ce7d1cf74117 completed April 18, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00b28b77188190b8d87fca1b5dde5d completed May 10, 2026, 4:30 p.m.
NEDg Description generation batch_6a00b32d2a588190b59bad56f8817bce completed May 10, 2026, 4:32 p.m.
NED2 Entity disambiguation (via description) batch_6a00b3d14b3c819081f435777f47eca3 completed May 10, 2026, 4:35 p.m.
Created at: April 10, 2026, 5:22 a.m.