Triple

T19800153
Position Surface form Disambiguated ID Type / Status
Subject Beinwil am See E475650 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Birrwil 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: Birrwil | Statement: [Beinwil am See, neighboringMunicipality, Birrwil]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Birrwil
Context triple: [Beinwil am See, neighboringMunicipality, Birrwil]
  • A. Birrwil chosen
    Birrwil is a small Swiss municipality in the canton of Aargau, known for its scenic location on the shores of Lake Hallwil.
  • B. Irlbach
    Irlbach is a small municipality in the Straubing-Bogen district of Bavaria, Germany, situated along the Danube River.
  • C. Bannwil
    Bannwil is a small Swiss municipality in the canton of Bern, situated in the Oberaargau region.
  • D. Borenore
    Borenore is a small rural locality in the Central West region of New South Wales, Australia, known for its agricultural surroundings and nearby limestone caves.
  • E. Wilsede
    Wilsede is a small village in the Lüneburg Heath region of Lower Saxony, Germany, known for its well-preserved heathland landscape and traditional car-free 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_69d8e51bc4208190a1c57d8c5d1b15e4 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e653cb865c81909696d2b37476f62f completed April 20, 2026, 4:26 p.m.
Created at: April 10, 2026, 1:49 p.m.