Using semantic unification to generate regular expressions from natural language
N Kushman, R Barzilay - 2013 - dspace.mit.edu
2013•dspace.mit.edu
We consider the problem of translating natural language text queries into regular
expressions which represent their meaning. The mismatch in the level of abstraction
between the natural language representation and the regular expression representation
make this a novel and challenging problem. However, a given regular expression can be
written in many semantically equivalent forms, and we exploit this flexibility to facilitate
translation by finding a form which more directly corresponds to the natural language. We …
expressions which represent their meaning. The mismatch in the level of abstraction
between the natural language representation and the regular expression representation
make this a novel and challenging problem. However, a given regular expression can be
written in many semantically equivalent forms, and we exploit this flexibility to facilitate
translation by finding a form which more directly corresponds to the natural language. We …
We consider the problem of translating natural language text queries into regular expressions which represent their meaning. The mismatch in the level of abstraction between the natural language representation and the regular expression representation make this a novel and challenging problem. However, a given regular expression can be written in many semantically equivalent forms, and we exploit this flexibility to facilitate translation by finding a form which more directly corresponds to the natural language. We evaluate our technique on a set of natural language queries and their associated regular expressions which we gathered from Amazon Mechanical Turk. Our model substantially outperforms a state-of-the-art semantic parsing baseline, yielding a 29% absolute improvement in accuracy.
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