PKU Paraphrase Bank: A Sentence-Level Paraphrase Corpus for Chinese

Pages: 814 - 826
Published: Jan 1, 2019
Abstract
One of the main challenges of conducting research on paraphrase is the lack of large-scale, high-quality corpus, which is particularly serious for non-English investigations. In this paper, we present a simple and effective unsupervised learning model that is able to automatically extract high-quality sentence-level paraphrases from multiple Chinese translations of the same source texts. By applying this new model, we obtain a large-scale...
Paper Details
Title
PKU Paraphrase Bank: A Sentence-Level Paraphrase Corpus for Chinese
Published Date
Jan 1, 2019
Pages
814 - 826
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.