Triple

T19057409
Position Surface form Disambiguated ID Type / Status
Subject Prignitz district E466433 entity
Predicate containsTown P847 FINISHED
Object Wittenberge 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: Wittenberge | Statement: [Prignitz district, containsTown, Wittenberge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wittenberge
Context triple: [Prignitz district, containsTown, Wittenberge]
  • A. Wittenberge chosen
    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.
  • B. Wittenberg
    Wittenberg is a historic German city best known as the cradle of the Protestant Reformation and the place where Martin Luther taught and preached.
  • 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 am Main
    Karlstadt am Main is a historic town in northern Bavaria, Germany, situated on the River Main and known for its medieval old town and surrounding wine-growing region.
  • E. Schmalkalden
    Schmalkalden is a historic town in the German state of Thuringia, known for its well-preserved medieval architecture and role in Reformation-era politics.
  • 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_69d8dd040fb881909af2a964f65ad208 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5dc0742288190a594be859184841a completed April 20, 2026, 7:55 a.m.
Created at: April 10, 2026, 12:03 p.m.