@inproceedings{sawada-etal-2020-coordination,
    title = "Coordination Boundary Identification without Labeled Data for Compound Terms Disambiguation",
    author = "Sawada, Yuya  and
      Wada, Takashi  and
      Shibahara, Takayoshi  and
      Teranishi, Hiroki  and
      Kondo, Shuhei  and
      Shindo, Hiroyuki  and
      Watanabe, Taro  and
      Matsumoto, Yuji",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://aclanthology.org/2020.coling-main.271",
    doi = "10.18653/v1/2020.coling-main.271",
    pages = "3043--3049",
    abstract = "We propose a simple method for nominal coordination boundary identification. As the main strength of our method, it can identify the coordination boundaries without training on labeled data, and can be applied even if coordination structure annotations are not available. Our system employs pre-trained word embeddings to measure the similarities of words and detects the span of coordination, assuming that conjuncts share syntactic and semantic similarities. We demonstrate that our method yields good results in identifying coordinated noun phrases in the GENIA corpus and is comparable to a recent supervised method for the case when the coordinator conjoins simple noun phrases.",
}