自然语言的语义处理器

J. Weber, P. C. Berry, W. Hagamen, K. Iverson
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引用次数: 1

摘要

从英语文本中提取、表达和利用意义的问题一直是一个难以解决的问题。语义解析允许对领域定义良好的复杂问题做出有效和相关的响应。使用的语义网是一个三行数字矩阵。网络的每一列代表一个关于域的断言。每个单词的含义都包含在关联中(指向域内事物名称的指针)。这些指针的交集用于定义每个短语。必要时,通过常识的实施,将歧义进一步减少,将解释限制在可能作为每个动词的主语或宾语的那些意义上。通过将一个子句的结果作为下一个子句的参数传递来处理多个嵌入子句。通过这种方法,复杂的表达式可以简化为单个标记。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A semantic processor for natural language
The problem of the extraction, representation, and utilization of meaning from English text has been elusive. Semantic parsing permits effective and relevant response to complex questions where the domain is well defined. The semantic net used is a three-row numeric matrix. Each column of the net represents an assertion about the domain. The meanings of each word are contained in associations (pointers to the names of things within the domain). The intersection of these pointers is used to define each phrase. Ambiguity is further reduced, when necessary, by an implementation of common sense-limiting the interpretations to those meanings that may be associated as the subject or object of each verb. Multiply embedded clauses are processed by passing the result of one clause as an argument for the next. By this means, complex expressions can be reduced to a single token.<>
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