Language Parsing
Overview
Language parsing group at Natural Language Processing Lab are working on Chinese Word Segmentation, Part-of-Speech Tagging, Constituent-based Syntactic Parsing, and Semantic Role Labeling.
People
Chinese Word Segmentation & Part-of-Speech Tagging
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Chinese word segmentation is defined to split a raw sentence into words with appropriate delimiters. Part-of-Speech tagging is defined to assign appropriate Part-of-Speech tags to words in sentences. Research at the lab focuses on two directions: 1) how to apply machine learning methods to get better practical-world systems; 2) how to combine multiple resources (maybe) with different annotation standards.
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Software: to be available
Constituent-based Syntactic Parsing
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Constituent-based Syntactic parsing aims to assign parse tree(s) to input sentences. Generally, input sentences are preprocessed with word segmentation (if for asian languages, ex. Chinese) and part-of-speech tagging. Research at the lab focues on syntactic parsing for Chinese.
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Software: to be available
Semantic Role Labeling
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Semantic role labeling is used to identify predicate-argument structure(s) in a sentence. Generally semantic role labeling uses syntactic parse tree(s) as input. The research focus of our lab is to jointly learn syntactic parsing and semantic role labeling. Moreover, we are seeking extensive applications of semantic role labeling.
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Software: to be available
Publication
Muhua Zhu, Huizhen Wang, and Jingbo Zhu. Label Correspondence Learning for Part-of-Speech Annotation Transformation. Proceedings of the 18th ACM International Conference on Information and Knowledge Management ( CIKM'09, short paper).
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