Improving our understanding of and creating computational analyses for natural language texts
Faculty involved: Baldridge, Beaver and Erk
Research assistants: Moon
Funding agency: New York Community Trust
Improving the efficiency of annotation for language documentation and description using natural language processing and machine learning.
Faculty involved: Baldridge, Erk
Research assistants: Moon, Palmer
Funding agency: NSF
This project aims to provide a graphical interface for automatic semantic analysis (word sense disambiguation, semantic role labeling) for graduate and undergraduate teaching.
Faculty involved: Erk
Research assistants: Brown, Fountain, Ponvert, Young
Funding agency: LAITS
Investigation into robust discourse parsing of newspaper texts and the integration of rich information sources in coreference resolution, including discourse structure.
Faculty involved: Asher, Baldridge
Funding agency: NSF
The aim of the TexTime project is to improve our understanding of and create computational analyses of events and entities evoked in natural language texts and the structure and progression of time over those events. This work will not only contribute to the scientific understanding of how time is conceptualized and communicated in language, but will lead to the development of tools to assist in cross-cultural information exchange.
Faculty involved: Baldridge
Funding agency: New York Community Trust