Processing of multi-word expressions (MWEs) is well known ‘pain in the neck’ of human language technology researchers. The problem of MWE treatment affects almost any natural language processing task, including different levels of text analysis and automated translation. It is extremely complicated task for machine translation (MT), as it includes identification, alignment and translation. Many on-line machine translation systems translate MWEs as phrases, not as one complex unit. In this paper several experiments are presented where possible ways how statistical MT system could learn translations are investigated. Although there is no significant improvement achieved in automatic evaluation, manual inspection of translations revealed some improvement in fluency and adequacy of translations.
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