Machine Learning Based Rules Compiler for Part-Of-Speech Tagging

原文（中文）

A computer-implemented method for a machine learning based rules compiler, the method comprising receiving machine learning generated ripple down rules, the ripple down rules comprising exception rules for tags in a tag set, the exception rules comprising tag string comparisons. The method further comprises compiling the ripple down rules into optimized computer code. Compiling the rules into computer code further comprises generating an enumeration statement for an enumeration containing the tag set, translating the exception rules for each tag in the tag set into if-else statements for a respective tag, including replacing the tag string comparisons with the enumeration; and generating a switch case statement for a current tag, the switch case statement having cases corresponding the tags in the tag set and including the if-else statements for the respective tag. The optimized computer code comprises the enumeration statement and the switch case statement.