# These exceptions are used to add NORM values based on a token's ORTH value.
# Individual languages can also add their own exceptions and overwrite them -
# for example, British vs. American spelling in English.

# Norms are only set if no alternative is provided in the tokenizer exceptions.
# Note that this does not change any other token attributes. Its main purpose
# is to normalise the word representations so that equivalent tokens receive
# similar representations. For example: $ and € are very different, but they're
# both currency symbols. By normalising currency symbols to $, all symbols are
# seen as similar, no matter how common they are in the training data.


NORM_EXCEPTIONS = {
    "R$": "$",  # Real
    "r$": "$",  # Real
    "Cz$": "$",  # Cruzado
    "cz$": "$",  # Cruzado
    "NCz$": "$",  # Cruzado Novo
    "ncz$": "$",  # Cruzado Novo
}