Publication
EMNLP 2017
Short paper
GrASP: Rich Patterns for Argumentation Mining
Abstract
We present the GrASP algorithm for au- tomatically extracting patterns that char- acterize subtle linguistic phenomena. To that end, GrASP augments each term of input text with multiple layers of linguis- tic information. These different facets of the text terms are systematically combined to reveal rich patterns. We report highly promising experimental results in several challenging text analysis tasks within the field of Argumentation Mining. We be- lieve that GrASP is general enough to be useful for other domains too.