Triple

T5469508
Position Surface form Disambiguated ID Type / Status
Subject Bern S-Bahn E122795 entity
Predicate connectsTo P845 FINISHED
Object Fribourg/Freiburg E44938 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: Fribourg/Freiburg | Statement: [Bern S-Bahn, connectsTo, Fribourg/Freiburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fribourg/Freiburg
Context triple: [Bern S-Bahn, connectsTo, Fribourg/Freiburg]
  • A. Fribourg chosen
    Fribourg is a bilingual Swiss canton in western Switzerland known for its medieval capital city and location at the cultural boundary between French- and German-speaking regions.
  • B. St. Gallen
    St. Gallen is a historic city in northeastern Switzerland renowned for its UNESCO-listed Abbey of Saint Gall and rich textile heritage.
  • C. Biel/Bienne
    Biel/Bienne is a bilingual (German-French) Swiss city in the canton of Bern, known for its watchmaking industry and location at the eastern end of Lake Biel.
  • D. Murten
    Murten is a historic bilingual town in the canton of Fribourg, Switzerland, known for its well-preserved medieval old town and lakeside setting on Lake Murten.
  • E. Uster
    Uster is a Swiss town and municipality in the canton of Zürich, known as a regional center near Lake Greifen with a mix of urban amenities and surrounding natural landscapes.
  • 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_69bd46459ff48190823377457bcf7128 completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd921b65f48190af7fcf89140f9ba8 completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf4893029081908a801c7a44872ebf completed March 22, 2026, 1:40 a.m.
Created at: March 20, 2026, 2:09 p.m.