Full-text processing
Tetsuya Nasukawa · 1996
Rich information for resolving ambiguities in sentence analysis, including various context-dependent problems, can be obtained by analyzing a simple set of parsed trees of each sentence in a text without constructing a precise model of the context through deep semantic analysis. Thus, processing a group of sentences together makes it possible to improve the accuracy of a practical natural language processing (NLP) system such as a machine translation system. In this paper, we describe a simple context model consisting of parsed trees of each sentence in a text, and its effectiveness for handling various problems in NLP such as the resolution of structural ambiguities, pronoun referents, and the focus of focusing subjects (e.g. also and only), as well as for adding supplementary phrases to some elliptical sentences.