Triple

T4824382
Position Surface form Disambiguated ID Type / Status
Subject Albrecht Bethe E107786 entity
Predicate givenName P17 FINISHED
Object Albrecht E73267 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: Albrecht | Statement: [Albrecht Bethe, givenName, Albrecht]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Albrecht
Context triple: [Albrecht Bethe, givenName, Albrecht]
  • A. Albrecht chosen
    Albrecht is a Germanic given name, historically borne by various nobles, artists, and scholars in German-speaking Europe.
  • B. Albrecht Schuch
    Albrecht Schuch is a German actor known for his acclaimed performances in film and television, including a prominent role in the 2022 adaptation of "All Quiet on the Western Front."
  • C. Karl Albrecht
    Karl Albrecht was a German businessman best known as the co-founder of the global discount supermarket chain Aldi.
  • D. John of Görlitz
    John of Görlitz was a 14th-century German prince of the House of Luxembourg who held the title of Duke of Görlitz and was a son of Holy Roman Emperor Charles IV.
  • E. Julius Echter von Mespelbrunn
    Julius Echter von Mespelbrunn was a 16th–17th century Prince-Bishop of Würzburg and Counter-Reformation leader known for his major role in expanding and reforming the University of Würzburg.
  • 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_69bd43fac8188190803f0327190621e4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6cadb2bc81909455149e46eb593a completed March 20, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5cb34004819086809b4a7071f4a5 completed March 21, 2026, 8:54 a.m.
Created at: March 20, 2026, 1:24 p.m.