Exploring Knowledge-Rich Solutions to Noun Phrase Coreference Resolution

Update Item Information
Publication Type poster
School or College Scientific Computing and Imaging Institute
Department Computing, School of
Creator Gilbert, Nathan Alan; Riloff, Ellen M.
Title Exploring Knowledge-Rich Solutions to Noun Phrase Coreference Resolution
Description Coreference resolution is the task of identifying coreferent expressions in text. Accurate coreference resolution can improve other tasks such as machine translation, information retrievel and document summarization. Currently, the best approaches involve some form of supervised Machine Learning algorithms, which requires annotated corpora. This requirement is expensive and time consuming. The initial stage of this project was to implement a state of the art supervised learning based coreference system. The general flow of this system is presented next, notice that for supervised learning systems, the classifier must be trained on annotated text.
Type Text; Image
Publisher University of Utah
Language eng
Bibliographic Citation Gilbert, N, & Riloff, E. (2010). Exploring Knowledge-Rich Solutions to Noun Phrase Coreference Resolution. University of Utah.
Rights Management (c) Nathan Gilbert & Ellen Riloff
Format Medium application/pdf
Format Extent 209,344 bytes
Identifier ir-main/14795
ARK ark:/87278/s68k7tsr
Setname ir_uspace
ID 707598
Reference URL https://collections.lib.utah.edu/ark:/87278/s68k7tsr
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