Triple

T12971718
Position Surface form Disambiguated ID Type / Status
Subject Kirkkonummi E321412 entity
Predicate hasTwinTown P919 FINISHED
Object Lörrach E578524 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: Lörrach | Statement: [Kirkkonummi, hasTwinTown, Lörrach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lörrach
Context triple: [Kirkkonummi, hasTwinTown, Lörrach]
  • A. Lörrach chosen
    Lörrach is a town in southwest Germany’s Baden-Württemberg state, near the borders with Switzerland and France, known for its proximity to Basel and its role as a regional economic and cultural center.
  • B. Wissembourg
    Wissembourg is a historic town in northeastern France’s Alsace region, known for its well-preserved medieval architecture and proximity to the German border.
  • C. Molsheim
    Molsheim is a historic town in northeastern France’s Grand Est region, known for its medieval architecture and as the birthplace of the Bugatti automobile brand.
  • D. Guebwiller
    Guebwiller is a commune in northeastern France known for its wine production and location at the foot of the Vosges mountains in the Alsace region.
  • E. Waldkirch
    Waldkirch is a small historic town in southwestern Germany’s Black Forest region, known for its scenic surroundings and traditional organ-building industry.
  • 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_69d97e418d548190be1c73db76cb3aa8 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1af38248190a85d0fa3a26c3d08 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 8:36 p.m.