压缩Penn树库语法
Compacting the Penn Treebank Grammar
摘要：
树库，如Penn Treebank（PTB），提供了一种获得广泛覆盖语法的简单方法：人们可以简单地从树库中的解析树中读取语法。虽然这样的语法很容易获得，但规则集随语料库大小的平方根增长率表明，派生的语法远不完整，如果存在某种限制，则需要更多的树库文本才能获得完整的语法。然而，我们提供了一个替代的解释，在树库内的结构规格不足。这一假设是探讨通过应用一种算法来压缩派生的语法，通过消除冗余的规则-规则的右手边可以被其他规则解析。所得到的紧凑的语法，这是显着小于完整的树库语法的大小，接近一个极限。然而，这样一个紧凑的语法并不能产生非常好的性能数据。一个版本的压缩算法考虑到规则概率的建议，这被认为是更多的语言动机。结合简单的阈值，这种方法可以用来给一个58%的减少语法的大小没有显着的变化，在分析性能，并可以产生一个69%的减少与一些收益的召回，但损失的精度。
英文摘要：
Treebanks, such as the Penn Treebank (PTB), offer a simple approach to obtaining a broad coverage grammar: one can simply read the grammar off the parse trees in the treebank. While such a grammar is easy to obtain, a square-root rate of growth of the rule set with corpus size suggests that the derived grammar is far from complete and that much more treebanked text would be required to obtain a complete grammar, if one exists at some limit. However, we offer an alternative explanation in terms of the underspecification of structures within the treebank. This hypothesis is explored by applying an algorithm to compact the derived grammar by eliminating redundant rules -- rules whose right hand sides can be parsed by other rules. The size of the resulting compacted grammar, which is significantly less than that of the full treebank grammar, is shown to approach a limit. However, such a compacted grammar does not yield very good performance figures. A version of the compaction algorithm taking rule probabilities into account is proposed, which is argued to be more linguistically motivated. Combined with simple thresholding, this method can be used to give a 58% reduction in grammar size without significant change in parsing performance, and can produce a 69% reduction with some gain in recall, but a loss in precision.
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