A Pronoun Anaphora Resolution System based on Factorial Hidden Markov Models
A Pronoun Anaphora Resolution System based on Factorial Hidden Markov Models
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发表时间：
2011-06
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通讯作者：
Dingcheng Li;Timothy Miller;William Schuler
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作者：
Dingcheng Li;Timothy Miller;William Schuler
提出了一种基于阶乘隐马尔可夫模型（fhmm）的有监督代词回指消解系统。其基本思想是fhmm的隐藏状态是一种显式短期记忆，具有包含最近描述的指涉物的先行缓冲。因此，一个被观察到的代词可以从隐藏缓冲区中找到它的先行词，或者就生成模型而言，隐藏缓冲区中的条目生成相应的代词。在ACE语料库上对实现该模型的系统进行了评价，取得了良好的性能。
This paper presents a supervised pronoun anaphora resolution system based on factorial hidden Markov models (FHMMs). The basic idea is that the hidden states of FHMMs are an explicit short-term memory with an antecedent buffer containing recently described referents. Thus an observed pronoun can find its antecedent from the hidden buffer, or in terms of a generative model, the entries in the hidden buffer generate the corresponding pronouns. A system implementing this model is evaluated on the ACE corpus with promising performance.