Collaborative Research on Knowledge Aquisition for Japanese-English Machine Translation

9303013格里什曼今年是蒙茅斯学院和纽约大学合作项目的第二年，该项目旨在收集日语和英语的源和目标平行语料库中的表达之间的对应关系，目的是推广这些对应关系，以制定在翻译系统中使用的规则。翻译系统的性能通常在很大程度上受到我们手动编码关于这种对应关系的信息的能力的限制。在这个项目中，源语言和目标语言的文本被解析，然后在句法上正规化，产生正则化的句法分析树。树匹配程序将源文本和目标文本中的对应树对齐，在源结构和目标结构之间产生一组详细的对应关系。然后定义一组子语言(语义)词类，并使用这些词类尽可能地概括这些对应关系；结果是翻译系统的转移阶段的一组规则。该方法使用日语和英语编写的相应编程语言手册。

9303013 Grishman This is the second year of a collaborative project between Monmouth College and New York University seeks to gather correspondences between expressions in source and target parallel corpora in Japanese and English with the objective of generalizing these correspondences to create rules for use in a translation system. The performance of translation systems has been often limited to a great extent by our ability to encode information about such correspondences manually. In this project the texts in the source and target languages are parsed and then syntactically regularized, producing regularized parse trees. A tree-matching procedure aligns the corresponding trees from the source and target texts, producing a set of detailed correspondences between source and target structures. A set of sublanguage (semantic) word classes is then defined and these correspondences are generalized to the extent possible using these word classes; the result is a set of rules for the transfer phase of a translation system. The approach uses corresponding programming language manuals written in Japanese and English.