@inproceedings{kim-etal-2018-utilizing,
    title = "Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs",
    author = "Kim, Eun-kyung  and
      Han, Kijong  and
      Kim, Jiho  and
      Choi, Key-Sun",
    editor = "Zhao, Dongyan",
    booktitle = "Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations",
    month = aug,
    year = "2018",
    address = "Santa Fe, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/C18-2011/",
    pages = "48--52",
    abstract = "This demo deals with the problem of capturing omitted arguments in relation extraction given a proper knowledge base for entities of interest. This paper introduces the concept of a salient entity and use this information to deduce omitted entities in the paragraph which allows improving the relation extraction quality. The main idea to compute salient entities is to construct a graph on the given information (by identifying the entities but without parsing it), rank it with standard graph measures and embed it in the context of the sentences."
}