@InProceedings{arase-tsujii:2017:EMNLP2017,
  author    = {Arase, Yuki  and  Tsujii, Jun'ichi},
  title     = {Monolingual Phrase Alignment on Parse Forests},
  booktitle = {Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {1--11},
  abstract  = {We propose an efficient method to conduct phrase alignment on parse forests for
	paraphrase detection. Unlike previous studies, our method identifies syntactic
	paraphrases under linguistically motivated grammar. In addition, it allows
	phrases to non-compositionally align to handle paraphrases with non-homographic
	phrase correspondences. 
	A dataset that provides gold parse trees and their phrase alignments is
	created. The experimental results confirm that the proposed method conducts
	highly accurate phrase alignment compared to human performance.},
  url       = {https://www.aclweb.org/anthology/D17-1001}
}