@inproceedings{kashefi-etal-2018-semantic,
    title = "Semantic Pleonasm Detection",
    author = "Kashefi, Omid  and
      Lucas, Andrew T.  and
      Hwa, Rebecca",
    editor = "Walker, Marilyn  and
      Ji, Heng  and
      Stent, Amanda",
    booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/N18-2036/",
    doi = "10.18653/v1/N18-2036",
    pages = "225--230",
    abstract = "Pleonasms are words that are redundant. To aid the development of systems that detect pleonasms in text, we introduce an annotated corpus of semantic pleonasms. We validate the integrity of the corpus with interannotator agreement analyses. We also compare it against alternative resources in terms of their effects on several automatic redundancy detection methods."
}