Noun Phrase Chunking for Turkish Using a Dependency Parser


Kutlu M., ÇİÇEKLİ İ.

30th International Symposium on Computer and Information Sciences (ISCIS), London, Canada, 21 - 24 September 2015, vol.363, pp.381-391 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 363
  • Doi Number: 10.1007/978-3-319-22635-4_35
  • City: London
  • Country: Canada
  • Page Numbers: pp.381-391

Abstract

Noun phrase chunking is a sub-category of shallow parsing that can be used for many natural language processing tasks. In this paper, we propose a noun phrase chunker system for Turkish texts. We use a weighted constraint dependency parser to represent the relationship between sentence components and to determine noun phrases. The dependency parser uses a set of hand-crafted rules which can combine morphological and semantic information for constraints. The rules are suitable for handling complex noun phrase structures because of their flexibility. The developed dependency parser can be easily used for shallow parsing of all phrase types by changing the employed rule set. The lack of reliable human tagged datasets is a significant problem for natural language studies about Turkish. Therefore, we constructed a noun phrase dataset for Turkish. According to our evaluation results, our noun phrase chunker gives promising results on this dataset.