在傳統的語法剖析中雖然基於幾率的前後文無關文法雖然在語法剖析中亦能取得較好表現，但卻無法處理需前後文語境才能解決的介系詞片語的二義性問題。本文提出了一種基於語法剖析樹片段與遞迴自動聯結記憶體的方法，同時考慮語法與語義線索，解決候選語法剖析樹中存在的二義性問題。

Traditional syntactic parsing such as using Probabilistic context free grammar (PCFG) parser, Stanford parser, etc. can achieve good performance on parsing natural language sentences. However, they usually suffer ambiguous problems in dealing with situations such as PP attachment that need semantic information to resolve. We propose a novel data-oriented fragment-based adaptive parsing method that combines both syntactic and semantic information with the help of parsing fragments and a recursive auto-associative memory (RAAM) that can disambiguate by selecting the most semantic plausible parse tree from ambiguous candidates.

Chapter 1 Introduction.......1
Chapter 2 Related works......3
Chapter 3 Method.............5
3.1 Parsing Fragments....5
3.2 RAAM.................6
3.3 Clustering...........8
Chapter 4 Experiment........11
Chapter 5 Conclusion........17
References..................18
Appendix....................20

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