Triple

T21903993
Position Surface form Disambiguated ID Type / Status
Subject S4 line E540882 entity
Predicate connects P390 FINISHED
Object Sihlwald 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: Sihlwald | Statement: [S4 line, connects, Sihlwald]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sihlwald
Context triple: [S4 line, connects, Sihlwald]
  • A. Sihlwald chosen
    Sihlwald is a large forest and nature reserve near Zurich, Switzerland, known for its protected, near-natural woodland and recreational hiking trails.
  • B. Wyssachen
    Wyssachen is a small rural municipality and village located in the Emmental region of the canton of Bern, Switzerland.
  • C. Griesalp
    Griesalp is a remote alpine settlement and hiking hub in the Bernese Oberland region of Switzerland, serving as a starting point for routes into the surrounding high mountains.
  • D. Brienz
    Brienz is a picturesque Swiss village in the Bernese Oberland, known for its lakeside setting on Lake Brienz and its traditional woodcarving craftsmanship.
  • E. Meisterschwanden
    Meisterschwanden is a municipality in the Swiss canton of Aargau, known for its scenic location near Lake Hallwil and its rural, lakeside character.
  • 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_69e0c47b4e8c81908c8076eaa4c8e4f2 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f121d4c0248190909172decd7cbc64 completed April 28, 2026, 9:08 p.m.
Created at: April 16, 2026, 7:26 p.m.