A Benchmark of Rule-Based and Neural Coreference Resolution in Dutch Novels and News

November 03, 2020 Β· Entered Twilight Β· πŸ› CRAC

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Authors Corbèn Poot, Andreas van Cranenburgh arXiv ID 2011.01615 Category cs.CL: Computation & Language Citations 18 Venue CRAC Repository https://github.com/andreasvc/crac2020 ⭐ 4 Last Checked 1 month ago
Abstract
We evaluate a rule-based (Lee et al., 2013) and neural (Lee et al., 2018) coreference system on Dutch datasets of two domains: literary novels and news/Wikipedia text. The results provide insight into the relative strengths of data-driven and knowledge-driven systems, as well as the influence of domain, document length, and annotation schemes. The neural system performs best on news/Wikipedia text, while the rule-based system performs best on literature. The neural system shows weaknesses with limited training data and long documents, while the rule-based system is affected by annotation differences. The code and models used in this paper are available at https://github.com/andreasvc/crac2020
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