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Flexible Non-Terminals for Dependency Tree-to-Tree Reordering

机译:依赖树到树重新排序的灵活非终端

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摘要

A major benefit of tree-to-tree over tree-to-string translation is that we can use target-side syntax to improve reordering. While this is relatively simple for binarized constituency parses, the reordering problem is considerably harder for dependency parses, in which words can have arbitrarily many children. Previous approaches have tackled this problem by restricting grammar rules, reducing the expressive power of the translation model. In this paper we propose a general model for dependency tree-to-tree reordering based on flexible non-terminals that can compactly encode multiple insertion positions. We explore how insertion positions can be selected even in cases where rules do not entirely cover the children of input sentence words. The proposed method greatly improves the flexibility of translation rules at the cost of only a 30% increase in decoding time, and we demonstrate a 1.2-1.9 BLEU improvement over a strong tree-to-tree baseline.
机译:与树到字符串的转换相比,树到树的主要优点是我们可以使用目标端语法来改善重新排序。尽管对于二元化选区分析而言,这相对简单,但对于依赖项分析而言,重排序问题就更加困难了,在依赖项分析中,单词可以具有任意多的子代。先前的方法通过限制语法规则,降低翻译模型的表达能力来解决此问题。在本文中,我们提出了一种基于可伸缩树结构树的重新排序的通用模型,该模型基于可紧凑编码多个插入位置的灵活非终端。我们探索即使在规则不能完全覆盖输入句子单词的子代的情况下如何选择插入位置。所提出的方法以仅将解码时间增加30%的代价极大地提高了翻译规则的灵活性,并且我们证明了在强大的树到树基线上可实现1.2-1.9 BLEU的改进。

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