Bootstrapping Lexical Choice via Multiple-Sequence Alignment

dc.creatorBarzilay, Regina
dc.creatorLee, Lillian
dc.date2002-05-25
dc.date.accessioned2026-07-07T03:18:27Z
dc.date.available2026-07-07T03:18:27Z
dc.descriptionAn 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 leverages 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.
dc.description8 pages; to appear in the proceedings of EMNLP-2002
dc.identifierhttps://arxiv.org/abs/cs/0205065
dc.identifierhttp://arxiv.org/abs/cs/0205065
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/31116
dc.subjectComputation and Language
dc.subject1.2.7
dc.titleBootstrapping Lexical Choice via Multiple-Sequence Alignment
dc.typetext

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