@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://aclanthology.org/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."
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    <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.</abstract>
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%0 Conference Proceedings
%T Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs
%A Kim, Eun-kyung
%A Han, Kijong
%A Kim, Jiho
%A Choi, Key-Sun
%Y Zhao, Dongyan
%S Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F kim-etal-2018-utilizing
%X 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.
%U https://aclanthology.org/C18-2011/
%P 48-52
Markdown (Informal)
[Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs](https://aclanthology.org/C18-2011/) (Kim et al., COLING 2018)
ACL