Extracting Syntactic Features from a Korean Treebank

Extraction of Tree Adjoining Grammars from a Treebank for Korean

We present the implementation of a system which extracts not only lexicalized grammars but also feature-based lexicalized grammars from Korean Sejong Treebank. We report on some practical experiments where we extract TAG grammars and tree schemata. Above all, full-scale syntactic tags and well-formed morphological analysis in Sejong Treebank allow us to extract syntactic features. In addition, ...

A Novel Approach to Conditional Random Field-based Named Entity Recognition using Persian Specific Features

Named Entity Recognition is an information extraction technique that identifies name entities in a text. Three popular methods have been conventionally used namely: rule-based, machine-learning-based and hybrid of them to extract named entities from a text. Machine-learning-based methods have good performance in the Persian language if they are trained with good features. To get good performanc...

Enriching the Syntactic Annotation of Korean Treebanks for Higher-level Processing: A Comparative Study of the Penn Korean Treebank and the 21st Sejong Korean Treebank

Feature Engineering in Persian Dependency Parser

Dependency parser is one of the most important fundamental tools in the natural language processing, which extracts structure of sentences and determines the relations between words based on the dependency grammar. The dependency parser is proper for free order languages, such as Persian. In this paper, data-driven dependency parser has been developed with the help of phrase-structure parser fo...

Syntactic Category Prediction for Improving Translation Quality in English-Korean Machine Translation

This paper proposes the syntactic category prediction for improving translation quality. In parsing using sentence segmentation, the segments are separately parsed and then the parsing results of each segment are combined to generate a global sentence structure. The syntactic category prediction guides the parser to identify relationships among segments and to select the correct parsing results...