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The automatic insertion of diacritics in electronic texts is necessary for a number of languages, including French, Romanian, Croatian, Sindhi, Vietnamese, etc. When diacritics are removed from a word and the resulting string of characters is not a word, it is easy to recover the diacritics. However, sometimes the resulting string is also a word, possibly with different grammatical properties or a...
Cross-lingual projection encounters two major challenges, the noise from word-alignment error and the syntactic divergences between two languages. To solve these two problems, a semi-supervised learning framework of cross-lingual projection is proposed to get better annotations using parallel data. Moreover, a projection model is introduced to model the projection process of labeling from the resource-rich...
Nominal entity recognition is a fundamental task in natural language processing. Semantic role labeling views a sentence as a predicate-arguments structure, which provides an alternative perspective for the boundary detection and type recognition of nominal entity. In this paper, we propose a nominal entity recognition method with semantic role labeling. First, a maximum entropy (ME) model is trained...
Conditional random fields (CRFs) have been used for many sequence labeling tasks and got excellent results. Further, the supervised model strongly depends on the huge training data. Active learning is a different way rather than relying on a large amount random sampling. However, random sampling constructively participates in the optimal choosing training examples. Based on different query strategies,...
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