@InProceedings{pathak-goyal-bhowmick:2016:NLPTEA2016,
  author    = {Pathak, Arkanath  and  Goyal, Pawan  and  Bhowmick, Plaban},
  title     = {A Two-Phase Approach Towards Identifying Argument Structure in Natural Language},
  booktitle = {Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {11--19},
  abstract  = {We propose a new approach for extracting argument structure from natural
	language texts that contain an underlying argument. Our approach comprises of
	two phases: Score Assignment and Structure Prediction. The Score Assignment
	phase trains models to classify relations between argument units (Support,
	Attack or Neutral). To that end, different training strategies have been
	explored. We identify different linguistic and lexical features for training
	the classifiers. Through ablation study, we observe that our novel use of
	word-embedding features is most effective for this task. The Structure
	Prediction phase makes use of the scores from the Score Assignment phase to
	arrive at the optimal structure. We perform experiments on three argumentation
	datasets, namely, AraucariaDB, Debatepedia and Wikipedia. We also propose two
	baselines and observe that the proposed approach outperforms baseline systems
	for the final task of Structure Prediction.},
  url       = {http://aclweb.org/anthology/W16-4903}
}