Abstract
In recent years, Interactive Argument Pair Identification has attracted widespread attention as an important task in argument mining. Existing methods for the task usually explicitly model the matching score between the argument pairs. However, identifying whether two arguments have an interactive relationship not only depends on the argument itself, but also usually requires its context to better grasp the views expressed by the two arguments. In the NLPCC-2021 shared task Argumentative Text Understanding for AI Debater, we participated in track 2 Interactive Argument Pair Identification in Online Forum and proposed ACE, A Context-Enhanced model which makes good use of the context information of the argument. In the end, we ranked 1st in this task, indicating the effectiveness of our model.
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Acknowledgements
This work was supported by Beijing Natural Science Foundation (4192057) and Science Foundation of Beijing Language and Culture University (the Fundamental Research Funds for the Central Universities: 21YJ040005).
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Wu, Y., Liu, P. (2021). ACE: A Context-Enhanced Model for Interactive Argument Pair Identification. In: Wang, L., Feng, Y., Hong, Y., He, R. (eds) Natural Language Processing and Chinese Computing. NLPCC 2021. Lecture Notes in Computer Science(), vol 13029. Springer, Cham. https://doi.org/10.1007/978-3-030-88483-3_46
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DOI: https://doi.org/10.1007/978-3-030-88483-3_46
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