تقرير
A Benchmark of Rule-Based and Neural Coreference Resolution in Dutch Novels and News
العنوان: | A Benchmark of Rule-Based and Neural Coreference Resolution in Dutch Novels and News |
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المؤلفون: | Poot, Corbèn, van Cranenburgh, Andreas |
سنة النشر: | 2020 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computation and Language |
الوصف: | 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 Comment: Accepted for CRAC 2020 @ COLING |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2011.01615 |
رقم الأكسشن: | edsarx.2011.01615 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |