Triple

T12968529
Position Surface form Disambiguated ID Type / Status
Subject Kamenz E321330 entity
Predicate hasTwinTown P919 FINISHED
Object Wittlich E808636 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: Wittlich | Statement: [Kamenz, hasTwinTown, Wittlich]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wittlich
Context triple: [Kamenz, hasTwinTown, Wittlich]
  • A. Wittlich chosen
    Wittlich is a small town in the Rhineland-Palatinate region of western Germany, known for its wine production and historic old town.
  • B. Röthlein
    Röthlein is a small municipality in the Schweinfurt district of Bavaria, Germany.
  • C. Delitzsch
    Delitzsch is a historic town in the German state of Saxony, known for its well-preserved medieval center and regional administrative role.
  • D. Wustermark
    Wustermark is a municipality in the Havelland district of Brandenburg, Germany, located west of Berlin and known for its mix of rural character and growing residential and commercial areas.
  • E. Leuenberg
    Leuenberg is a village in Switzerland known as the site where major European Protestant churches concluded the Leuenberg Agreement on church fellowship.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e407e5081909424fc0c22483c28 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc0b8188190a6a40bb4edf53e25 completed May 3, 2026, 4:14 a.m.
Created at: April 9, 2026, 8:33 p.m.