Triple

T21007293
Position Surface form Disambiguated ID Type / Status
Subject Lucerne–Wolhusen railway E517444 entity
Predicate endPoint P390 FINISHED
Object Wolhusen NE NERFINISHED

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: Wolhusen | Statement: [Lucerne–Wolhusen railway, endPoint, Wolhusen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolhusen
Context triple: [Lucerne–Wolhusen railway, endPoint, Wolhusen]
  • A. Wolhusen chosen
    Wolhusen is a municipality in the canton of Lucerne in central Switzerland, known as a regional transport hub and gateway to the Entlebuch region.
  • B. Sigriswil
    Sigriswil is a municipality in the canton of Bern, Switzerland, known for its scenic location above Lake Thun and views of the surrounding Alps.
  • C. Neuhausen
    Neuhausen is a locality that forms one of the subdivisions of the Bavarian municipality of Metten in Germany.
  • D. Reisiswil
    Reisiswil is a small rural municipality in the Oberaargau region of the canton of Bern in Switzerland.
  • E. Attiswil
    Attiswil is a municipality in the canton of Bern in Switzerland, located in the Oberaargau region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50192308190a284fcc89dd23a49 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e6fc3cc8648190b1a419ef734a69e6 completed April 21, 2026, 4:25 a.m.
Created at: April 16, 2026, 1:53 p.m.