A Probabilistic Context-free Grammar for Disambiguation in Morphological Parsing
A Probabilistic Context-free Grammar for Disambiguation in Morphological Parsing
复制标题
用于形态解析中消歧的概率上下文无关语法
DOI：
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发表时间：
1993
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通讯作者：
Josée S. Heemskerk
中科院分区：
文献类型：
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作者：
Josée S. Heemskerk
将单词分解为其组成部分时面临的主要问题之一是歧义：为一个输入单词生成多个分析，其中许多分析是不可信的。为了处理歧义，形态语法分析器MORPA被提供了概率上下文无关文法(PCFG)，即它结合了传统的上下文无关形态语法来过滤不符合语法的切分和基于概率的评分函数，该函数确定每次成功句法分析的可能性。因此，剩余的分析可以按照似是而非的标准排序。测试性能数据将表明，PCFG在形态分析中产生了良好的结果。MORPA是一个完全实现的解析器，用于文本到语音转换系统。
One of the major problems one is faced with when decomposing words into their constituent parts is ambiguity: the generation of multiple analyses for one input word, many of which are implausible. In order to deal with ambiguity, the MOR-phological Parser MORPA is provided with a probabilistic context-free grammar (PCFG), i.e. it combines a "conventional" context-free morphological grammar to filter out ungrammatical segmentations with a probability-based scoring function which determines the likelihood of each successful parse. Consequently, remaining analyses can be ordered along a scale of plausibility. Test performance data will show that a PCFG yields good results in morphological parsing. MORPA is a fully implemented parser developed for use in a text-to-speech conversion system.