An Empirical Study of Span Representations in Argumentation Structure Parsing (P19-1)
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Tatsuki Kuribayashi, Hiroki Ouchi, Naoya Inoue, Paul Reisert, Toshinori Miyoshi, Jun Suzuki, Kentaro Inui
| Challenge: | Argumentation structure parsing (ASP) is a task of identifying argumentation structures in argumentative text. |
| Approach: | They propose to exploit neural network-based span representations for ASP to improve performance . they also propose task-dependent extensions for a parser that can be used to parse arguments . |
| Outcome: | The proposed model outperforms neural network-based approaches for argumentation structure parsing (ASP) it also provides some challenging types of instances to be parsed. |
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