Triple

T19565488
Position Surface form Disambiguated ID Type / Status
Subject district of Lörrach E489570 entity
Predicate containsTown P847 FINISHED
Object Zell im Wiesental 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: Zell im Wiesental | Statement: [district of Lörrach, containsTown, Zell im Wiesental]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zell im Wiesental
Context triple: [district of Lörrach, containsTown, Zell im Wiesental]
  • A. Zell im Wiesental chosen
    Zell im Wiesental is a small town in the Black Forest region of southwestern Germany, known as the birthplace of Constanze Mozart, the wife of composer Wolfgang Amadeus Mozart.
  • B. Dinkelscherben
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • C. Bad Waldliesborn
    Bad Waldliesborn is a spa village in the German region of Westphalia, known for its therapeutic mineral springs and health tourism.
  • D. Lorchhausen
    Lorchhausen is a small district of the town of Lorch in the Rheingau region of Hesse, Germany, known for its winegrowing and scenic location along the Rhine River.
  • E. Steinwiesen
    Steinwiesen is a small municipality in northern Bavaria, Germany, known for its location in the Franconian Forest and its traditional rural character.
  • 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_69d8e8dc5d8c8190a6d7bd8864f43ca0 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e63f777cf081909312b46ac09bce7c completed April 20, 2026, 3 p.m.
Created at: April 10, 2026, 1:42 p.m.