Triple

T16408752
Position Surface form Disambiguated ID Type / Status
Subject Krefeld E398502 entity
Predicate hasDistrict P459 FINISHED
Object Uerdingen E268210 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: Uerdingen | Statement: [Krefeld, hasDistrict, Uerdingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uerdingen
Context triple: [Krefeld, hasDistrict, Uerdingen]
  • A. Uerdingen chosen
    Uerdingen is a district of the German city of Krefeld, known historically for its chemical industry and location along the Rhine River.
  • B. Weikersheim
    Weikersheim is a small historic town in the Tauber Valley of Baden-Württemberg, Germany, known for its Renaissance castle and well-preserved old town.
  • C. Badenweiler
    Badenweiler is a spa town in southwestern Germany’s Black Forest region, known for its thermal baths and as the place where Russian writer Anton Chekhov died.
  • D. Dornheim
    Dornheim is a small village in Thuringia, Germany, historically noted as the place where Johann Sebastian Bach married Maria Barbara Bach.
  • E. Bruchsal
    Bruchsal is a town in the state of Baden-Württemberg in southwestern Germany, known for its baroque palace and asparagus cultivation.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32870e44c8190aae7bc6e6022ceb7 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00bafe159c8190b66d2cd21b8ddb88 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:09 a.m.