Triple

T15256295
Position Surface form Disambiguated ID Type / Status
Subject Germany–Switzerland border E364653 entity
Predicate hasBorderCity P15361 FINISHED
Object Waldshut-Tiengen E447495 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: Waldshut-Tiengen | Statement: [Germany–Switzerland border, hasBorderCity, Waldshut-Tiengen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waldshut-Tiengen
Context triple: [Germany–Switzerland border, hasBorderCity, Waldshut-Tiengen]
  • A. Waldshut-Tiengen chosen
    Waldshut-Tiengen is a town in southwestern Germany near the Swiss border, formed by the merger of Waldshut and Tiengen and known for its historic old town and Rhine River setting.
  • B. Wiesloch
    Wiesloch is a town in the Rhine-Neckar district of Baden-Württemberg, Germany, known for its historical center and role as a regional commercial hub.
  • C. Bochingen
    Bochingen is a village and district of the town Oberndorf am Neckar in the state of Baden-Württemberg in southwestern Germany.
  • D. Hitzkirch
    Hitzkirch is a municipality in the canton of Lucerne in central Switzerland, known for its scenic setting near Lake Baldegg.
  • E. Ettlingen
    Ettlingen is a historic town in the state of Baden-Württemberg in southwestern Germany, known for its well-preserved old town and proximity to the city of Karlsruhe.
  • 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_69d85a0f08408190b3c3259ae35d79d2 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0084b97908190b3bf7ea7bd75bdc0 completed April 15, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a63464c8190afab59257c6a2095 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:13 a.m.