Year: 2020
Type: conference-paper
Abstract: Zero pronoun recovery and resolution aim at recovering the dropped pronoun and pointing out its anaphoric mentions, respectively.We propose to better explore their interaction by solving both tasks together, while the previous work treats them separately.For zero pronoun resolution, we study this task in a more realistic setting, where no parsing trees or only automatic trees are available, while most previous work assumes gold trees.Experiments on two benchmarks show that joint modeling significantly outperforms our baseline that already beats the previous state of the arts.
Authors: Linfeng Song, Kun Xu, Yue Zhang, Jianshu Chen, Dong Yu
Institution: Westlake University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W3035736543