Triple

T1475303
Position Surface form Disambiguated ID Type / Status
Subject Wittenberg E30826 entity
Predicate hasNickname P39 FINISHED
Object Lutherstadt Wittenberg E30826 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: Lutherstadt Wittenberg | Statement: [Wittenberg, hasNickname, Lutherstadt Wittenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lutherstadt Wittenberg
Context triple: [Wittenberg, hasNickname, Lutherstadt Wittenberg]
  • A. Wittenberg chosen
    Wittenberg is a historic German city best known as the cradle of the Protestant Reformation and the place where Martin Luther taught and preached.
  • B. Eisleben
    Eisleben is a historic town in the German state of Saxony-Anhalt, best known as the birthplace of Protestant Reformer Martin Luther.
  • C. Heidelberg
    Heidelberg is a historic university city in southwestern Germany renowned for its picturesque old town, castle ruins, and one of Europe’s oldest universities.
  • D. Eisenach
    Eisenach is a historic town in central Germany best known for its associations with Martin Luther and as the birthplace of composer Johann Sebastian Bach.
  • E. Regensburg
    Regensburg is a historic city in southeastern Germany known for its well-preserved medieval old town on the Danube River.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c602387c8190b97a20c8e05e3d16 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad1ca21f288190b5f6f9a5895cdcf0 completed March 8, 2026, 6:52 a.m.
Created at: March 1, 2026, 8:11 p.m.