Abstract
An important reason to prefer dependency parsing over classical phrased based methods, especially for languages such as Persian, with the property of being “free word order”, is that this particular property has a negative impact on the accuracy of conventional parsing methods. In Persian, some words such as adverbs can freely be moved within a sentence without affecting its correctness or meaning. In this paper, we illustrate the robustness of dependency parsing against this particular problem by training two well-known dependency parsers, namely MST Parser and Malt Parser, using a Persian dependency corpus called Dadegan. We divided the corpus into two separate parts including only projective sentences and only non-projective sentences, which are corelated with the free word order property. As our results show, MST Parsing is not only more tolerant than Malt Parsing against the free word order problem, but it is also in general a more accurate technique.
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Falavarjani, S.A.M., Ghassem-Sani, G. (2015). Advantages of Dependency Parsing for Free Word Order Natural Languages. In: Italiano, G.F., Margaria-Steffen, T., Pokorný, J., Quisquater, JJ., Wattenhofer, R. (eds) SOFSEM 2015: Theory and Practice of Computer Science. SOFSEM 2015. Lecture Notes in Computer Science, vol 8939. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46078-8_42
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DOI: https://doi.org/10.1007/978-3-662-46078-8_42
Publisher Name: Springer, Berlin, Heidelberg
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