Adaptive Sentence Boundary Disambiguation

David D. Palmer; Marti A. Hearst

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arXiv · cmp-lg/9411022

Adaptive Sentence Boundary Disambiguation

David D. Palmer·Marti A. Hearst

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Abstract

Labeling of sentence boundaries is a necessary prerequisite for many natural language processing tasks, including part-of-speech tagging and sentence alignment. End-of-sentence punctuation marks are ambiguous; to disambiguate them most systems use brittle, special-purpose regular expression grammars and exception rules. As an alternative, we have developed an efficient, trainable algorithm that uses a lexicon with part-of-speech probabilities and a feed-forward neural network. After training for less than one minute, the method correctly labels over 98.5\% of sentence boundaries in a corpus of over 27,000 sentence-boundary marks. We show the method to be efficient and easily adaptable to different text genres, including single-case texts.

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David D. Palmer, Marti A. Hearst. 1994-11-22. Adaptive Sentence Boundary Disambiguation. https://arxiv.org/abs/cmp-lg/9411022

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