Triple

T5469509
Position Surface form Disambiguated ID Type / Status
Subject Bern S-Bahn E122795 entity
Predicate connectsTo P845 FINISHED
Object Belp E399788 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: Belp | Statement: [Bern S-Bahn, connectsTo, Belp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Belp
Context triple: [Bern S-Bahn, connectsTo, Belp]
  • A. Belp chosen
    Belp is a municipality in the canton of Bern in Switzerland, situated near the city of Bern and known for hosting Bern Airport.
  • B. Aosta
    Aosta is a historic town in northwestern Italy known as the capital of the Aosta Valley region and for its well-preserved Roman and medieval architecture.
  • C. Blevio
    Blevio is a small lakeside municipality in the Province of Como, Lombardy, Italy, situated on the eastern shore of Lake Como.
  • D. Luzech
    Luzech is a commune in southwestern France known for its scenic location on a tight meander of the Lot River and its surrounding vineyards and historic sites.
  • E. Bernex
    Bernex is a municipality in western Switzerland located near the city of Geneva, known for its semi-rural character and surrounding vineyards.
  • 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.