Simpler unsupervised POS tagging with bilingual projections
Simpler unsupervised POS tagging with bilingual projections
复制标题
使用双语投影实现更简单的无监督 POS 标记
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Pavel Pecina
中科院分区：
文献类型：
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作者：
Long Duong;Paul Cook;Steven Bird;Pavel Pecina
我们提出了一种基于词对齐双语平行语料库中标签投影的无监督词性标记方法。与Das和Petrov现有的最先进的方法相比，我们开发了一种更简单的方法，通过从平行语料库中自动识别“好”的训练句子并进行自我训练。在八种语言的实验结果中，我们的方法达到了最先进的结果。
We present an unsupervised approach to part-of-speech tagging based on projections of tags in a word-aligned bilingual parallel corpus. In contrast to the existing state-of-the-art approach of Das and Petrov, we have developed a substantially simpler method by automatically identifying “good” training sentences from the parallel corpus and applying self-training. In experimental results on eight languages, our method achieves state-of-the-art results.