Triple

T21219149
Position Surface form Disambiguated ID Type / Status
Subject Leonhard Hutter E522918 entity
Predicate placeOfDeath P21 FINISHED
Object Wittenberg 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: Wittenberg | Statement: [Leonhard Hutter, placeOfDeath, Wittenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wittenberg
Context triple: [Leonhard Hutter, placeOfDeath, 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. Wittenberge
    Wittenberge is a small town in the state of Brandenburg in northeastern Germany, situated on the Elbe River and known for its historic industrial architecture and riverside setting.
  • C. Village of Wittenberg
    The Village of Wittenberg is a small rural community in central Wisconsin known for its agricultural surroundings and local small-town character.
  • D. Karlstadt
    Karlstadt is the former German name for the Croatian city of Karlovac, a historic fortress town located at the confluence of four rivers.
  • E. Wittenberg University
    Wittenberg University is a private liberal arts college known for its strong undergraduate programs and historic campus in Springfield, Ohio.
  • 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_69e0b511ed84819099b449b4a111085c completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e73476d93481909c6c99dcc0b16123 completed April 21, 2026, 8:25 a.m.
Created at: April 16, 2026, 3:42 p.m.