@InProceedings{muzny-EtAl:2017:EACLlong,
  author    = {Muzny, Grace  and  Fang, Michael  and  Chang, Angel  and  Jurafsky, Dan},
  title     = {A Two-stage Sieve Approach for Quote Attribution},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {460--470},
  abstract  = {We present a deterministic sieve-based system for attributing quotations in
	literary text and a new dataset: QuoteLi3. Quote attribution, determining who
	said what in a given text, is important for tasks like creating dialogue
	systems, and in newer areas like computational literary studies, where it
	creates opportunities to analyze novels at scale rather than only a few at a
	time. We release QuoteLi3, which contains more than 6,000 annotations linking
	quotes to speaker mentions and quotes to speaker entities, and introduce a new
	algorithm for quote attribution. Our two-stage algorithm first links quotes to
	mentions, then mentions to entities. Using two stages encapsulates difficult
	sub-problems and improves system performance. The modular design allows us to
	tune for overall performance or higher precision, which is useful for many
	real-world use cases. Our system achieves an average F-score of 87.5 across
	three novels, outperforming previous systems, and can be tuned for precision of
	90.4 at a recall of 65.1.},
  url       = {http://www.aclweb.org/anthology/E17-1044}
}