  We analyze the information provided by the word embeddings about the
grammatical gender in Swedish. We wish that this paper may serve as one of the
bridges to connect the methods of computational linguistics and general
linguistics. Taking nominal classification in Swedish as a case study, we first
show how the information about grammatical gender in language can be captured
by word embedding models and artificial neural networks. Then, we match our
results with previous linguistic hypotheses on assignment and usage of
grammatical gender in Swedish and analyze the errors made by the computational
model from a linguistic perspective.
