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Bootstrapping Lexical Choice via Multiple-Sequence Alignment

Barzilay, Regina; Lee, Lillian

An important component of any generation system is the mapping dictionary, a lexicon of elementary semantic expressions and corresponding natural language realizations. Typically, labor-intensive knowledge-based methods are used to construct the dictionary. We instead propose to acquire it automatically via a novel multiple-pass algorithm employing multiple-sequence alignment, a technique commonly used in bioinformatics. Crucially, our method lever-ages latent information contained in multi-parallel corpora --- datasets that supply several verbalizations of the corresponding semantics rather than just one.We used our techniques to generate natural language versions of computer-generated mathematical proofs, with good results on both a per-component and overall-output basis. For example, in evaluations involving a dozen human judges, our system produced output whose readability and faithfulness to the semantic input rivaled that of a traditional generation system.

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Academic Units
Computer Science
Publisher
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing
Published Here
May 10, 2013