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Learning a Compositional Semantics for Freebase with an Open Predicate Vocabulary
2015
Transactions of the Association for Computational Linguistics
We present an approach to learning a model-theoretic semantics for natural language tied to Freebase. Crucially, our approach uses an open predicate vocabulary, enabling it to produce denotations for phrases such as "Republican front-runner from Texas" whose semantics cannot be represented using the Freebase schema. Our approach directly converts a sentence's syntactic CCG parse into a logical form containing predicates derived from the words in the sentence, assigning each word a consistent
doi:10.1162/tacl_a_00137
fatcat:vuoo5747drfkdmjaa344kdli6q