CofeehousePy/services/corenlp/doc/tokensregex/examples/retokenize.txt

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# Uses TokensRegex library to split further split tokens with -
# Map variable names to annotation keys
tokens = { type: "CLASS", value: "edu.stanford.nlp.ling.CoreAnnotations$TokensAnnotation" }
# Indicates matched expressions should replace the tokens annotation
options.matchedExpressionsAnnotationKey = tokens;
# Indicates that the matched expressions and tokens should be combined
options.extractWithTokens = TRUE;
# Indicates that the matched expressions should be flattened to be just tokens
options.flatten = TRUE;
# Mark units
# Define ruleType to be over tokens
ENV.defaults["ruleType"] = "tokens"
# Case insensitive pattern matching (see java.util.regex.Pattern flags)
ENV.defaultStringPatternFlags = 2
# Indicates that after matching, and computing the result, the result should be placed in the tokens annotation
ENV.defaultResultAnnotationKey = tokens
# Define rule where upon matching tokens with -, the matched token is split
{ pattern: ( /.+-.+/ ), result: Split($0[0], /-/, TRUE) }