Incorporating Statistical Information of Lexical Dependency into a Rule-Based Parser
Year: 2009
Type: conference-paper
Abstract: . This paper presents a method to incorporate statistical information into a rule-based parser to resolve syntactic ambiguities. We extract the statistical information from the Penn Treebank, and apply the information to the rule-based parser. For the extraction of the statistical information the tag conversion is needed because of the disagreement of the tags and the bracketing style. We will show the effect of the tag conversion with experiments. The final result shows about 7 % error rate reduction in the dependency evaluation. We will also show how much each type of statistical information affects the parsing performance.
Authors: Yoon‐Hyung Roh, Kiyoung Lee, Young-Gil Kim
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2122215833