Person Name Extraction From Turkish Financial News Text Using Local Grammar-Based Approach

Local grammar approach relies on constructing polylexical units having frozen characteristics. It has recently been shown to be superior to other named entity extraction approaches including the probabilistic, the symbolic, and the hybrid approach in terms of being able to work with untagged corpora and has successfully been applied to English, Portuguese, Korean, French and Chinese texts. In this paper, we evaluated local grammar-based approach on Turkish financial texts. We have found that although the method is successful in finding person names, the construction of frozen expressions for person name extraction is rather difficult, which can be attributed to that of Turkish word formations.