@inproceedings{meged-etal-2020-paraphrasing,
    title = "Paraphrasing vs Coreferring: Two Sides of the Same Coin",
    author = "Meged, Yehudit  and
      Caciularu, Avi  and
      Shwartz, Vered  and
      Dagan, Ido",
    editor = "Cohn, Trevor  and
      He, Yulan  and
      Liu, Yang",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2020.findings-emnlp.440/",
    doi = "10.18653/v1/2020.findings-emnlp.440",
    pages = "4897--4907",
    abstract = "We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. First, we used annotations from an event coreference dataset as distant supervision to re-score heuristically-extracted predicate paraphrases. The new scoring gained more than 18 points in average precision upon their ranking by the original scoring method. Then, we used the same re-ranking features as additional inputs to a state-of-the-art event coreference resolution model, which yielded modest but consistent improvements to the model`s performance. The results suggest a promising direction to leverage data and models for each of the tasks to the benefit of the other."
}