Triple

T17591234
Position Surface form Disambiguated ID Type / Status
Subject Lungern E428451 entity
Predicate hasNeighboringMunicipality P224 FINISHED
Object Meiringen 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: Meiringen | Statement: [Lungern, hasNeighboringMunicipality, Meiringen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Meiringen
Context triple: [Lungern, hasNeighboringMunicipality, Meiringen]
  • A. Meiringen chosen
    Meiringen is a Swiss alpine town in the Bernese Oberland, known for its dramatic mountain scenery, Reichenbach Falls, and association with Sherlock Holmes.
  • B. Orscheid
    Orscheid is a small subdistrict within the Aegidienberg area of Bad Honnef in North Rhine-Westphalia, Germany.
  • C. Gimmelwald
    Gimmelwald is a small, traditional Swiss alpine village known for its dramatic mountain scenery and tranquil, car-free atmosphere in the Bernese Oberland.
  • D. Kiental
    Kiental is a picturesque alpine valley and village in the Bernese Oberland region of Switzerland, known for its dramatic mountain scenery and hiking opportunities.
  • E. Tannheim
    Tannheim is a small municipality in the district of Biberach in the German state of Baden-Württemberg, known for its rural character and Swabian cultural heritage.
  • 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e469e6e3888190b73a5b6d7e8c0a55 completed April 19, 2026, 5:36 a.m.
Created at: April 10, 2026, 5:51 a.m.