K-Best A* Parsing

K-Best A* Parsing
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K-Best A* 解析

DOI:
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发表时间:
2009
期刊:
Annual Meeting of the Association for Computational Linguistics
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通讯作者:
D. Klein
D. Klein
中科院分区:
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文献类型:
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作者:
Adam Pauls;D. Klein

文献摘要

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A*分析通过抑制不太可能的1-Best项来提高1-Best搜索的效率。现有的k-Best提取方法可以有效地搜索顶级派生,但只能在穷举1-Best通过之后才能找到。我们提出了一种统一的k-Best A*句法分析算法,该算法在保持K-Best抽取效率的同时,给出了A*方法的加速。我们的算法在相同的条件下产生了最优的k-Best语法分析,这与1-Best A*语法分析器中的最优条件相同。根据经验,在一系列语法类型上,提取最佳k-Best列表的速度比使用其他方法快得多。
A* parsing makes 1-best search efficient by suppressing unlikely 1-best items. Existing k-best extraction methods can efficiently search for top derivations, but only after an exhaustive 1-best pass. We present a unified algorithm for k-best A* parsing which preserves the efficiency of k-best extraction while giving the speed-ups of A* methods. Our algorithm produces optimal k-best parses under the same conditions required for optimality in a 1-best A* parser. Empirically, optimal k-best lists can be extracted significantly faster than with other approaches, over a range of grammar types.