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Baseball: an automatic question-answerer
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Question Answering (QA) systems provide efficient means for retrieval of information, which in many cases more directly address users' information needs. The performance of a QA system crucially depends on its ability to correctly classify the query question according to the expected answer type. This paper addresses the problem of a question classification for the Croatian language, as a first step towards building an open-domain QA system. We compare different machine learning classifiers on a Croatian test collection based on a two-level question taxonomy. The evaluation results are encouraging and comparable to state-of-the-art results for other languages: accuracy is over 80% for coarse-grained classification and almost 70% for fine-grained classification.