Signal and Data Processing

In this paper, the role of Part-of-Speech (POS) tagging for parsing in automatic processing of the Persian language is studied. To this end, the impact of the quality of POS tagging as well as the impact of the quantity of information available in the POS tags on parsing are studied. To reach the goals, three parsing scenarios are proposed and compared. In the first scenario, the parser assigns the POS tags firstly and then it parses the input sentence. In the second scenario, an external POS tagger is usedto assign the tags, then the sentence is parsed. In the third scenario, the parser uses the gold standard POS tags to parse the input sentence. In this study, various evaluation metrics are used to show the impacts from different points of views. The experimental results show that the quality of the POS tagger and the quantity of the information available in the POS tags have a direct effect on the parsing performance. The high quality of the POS tags causes error reduction in parsing and also it increases parsing performance. Moreover, lack ofmorphological -syntactic information in the POS tags has a high negative impact on parsing performance. This impact is more pronounced than the impact of POS tagger performance.