LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning

Andrew Bennett, Timothy Baldwin, Jey Han Lau, Diana McCarthy, Francis Bond. LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning. In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7-12, 2016, Berlin, Germany, Volume 1: Long Papers. The Association for Computer Linguistics, 2016. [doi]

@inproceedings{BennettBLMB16,
  title = {LexSemTm: A Semantic Dataset Based on All-words Unsupervised Sense Distribution Learning},
  author = {Andrew Bennett and Timothy Baldwin and Jey Han Lau and Diana McCarthy and Francis Bond},
  year = {2016},
  url = {http://aclweb.org/anthology/P/P16/P16-1143.pdf},
  researchr = {https://researchr.org/publication/BennettBLMB16},
  cites = {0},
  citedby = {0},
  booktitle = {Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016, August 7-12, 2016, Berlin, Germany, Volume 1: Long Papers},
  publisher = {The Association for Computer Linguistics},
  isbn = {978-1-945626-00-5},
}