Triple

T19408319
Position Surface form Disambiguated ID Type / Status
Subject Ludwig Yorck von Wartenburg E485520 entity
Predicate hasPartInName P5298 FINISHED
Object Yorck NE NERFINISHED

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: Yorck | Statement: [Ludwig Yorck von Wartenburg, hasPartInName, Yorck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yorck
Context triple: [Ludwig Yorck von Wartenburg, hasPartInName, Yorck]
  • A. Yorck von Wartenburg chosen
    Yorck von Wartenburg was a Prussian field marshal renowned for his decisive role in the Napoleonic Wars, particularly in leading Prussian forces during key campaigns of the War of the Sixth Coalition.
  • B. Leberecht
    Leberecht is the given name of the 19th-century German astronomer Wilhelm Tempel, known for discovering several comets and asteroids.
  • C. Philipp von Westphalen
    Philipp von Westphalen was a German nobleman and politician who served as Minister of the Interior of Prussia in the mid-19th century.
  • D. Ludwig von Westphalen
    Ludwig von Westphalen was a Prussian aristocrat and government official best known as the father-in-law and early intellectual influence of Karl Marx.
  • E. Hardenberg
    Hardenberg is a municipality in the Dutch province of Overijssel, known for its rural landscapes, small towns, and location near the German border.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62af331108190b6b25ef8f386826e completed April 20, 2026, 1:32 p.m.
Created at: April 10, 2026, 1:36 p.m.