PhD Dissertation: Developing and Applying an Integrated Semantic Framework for Natural Language Understanding
There is much active research in Computational Linguistics on deep semantics of natural language.
Various tools, methods and technologies have been developed for extracting and manipulating information from textual data.
these technologies have proven to be useful for many purposes, they are
mainly based on separated modular architectures and thus are subjected
In this research, I will study the
state-of-the-art approaches for computational semantic analysis and
introduce a new integrated semantic representation for such purposes.
integrating information from various perspectives such as lexical
semantics, structural semantics, and knowledge bases, we expect to
achieve better analyses in core tasks such as word-sense disambiguation,
parse ranking and knowledge extraction.
A prototype system will be
developed usingHead-driven Phrase Structure Grammar (HPSG: Sag, Wasow,
& Bender, 2003) Minimal Recursion Semantics (MRS: Copestake,
Flickinger, Sag, & Pollard, 2005) and WordNet (WN: Fellbaum, 1998).