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Phrase-based statistical machine translation systems can generate translations of reasonable quality in the case of language pairs with similar structure and word order. However, if the languages are more distant from a grammatical point of view, the quality of translations is much behind the expectations, since the baseline translation system cannot cope(More)
In this paper a Moses SMT toolkit-based language-independent complete morphological annotation tool is presented called HuLaPos2. Our system performs PoS tagging and lemmatization simultaneously. Amongst others, the algorithm used is able to handle phrases instead of unigrams, and can perform the tagging in a not strictly left-to-right order. With utilizing(More)
Part-of-speech tagging is a fundamental task of natural language processing. For languages with a very rich agglutinating morphology, generic PoS tagging algorithms do not yield very high accuracy due to data sparseness issues. Though integrating a morphological analyzer can efficiently solve this problem, this is a resource-intensive solution. In this(More)
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