The following paper received a best paper award of the Journal of Natural Language Processing (2020/3) †

• 栗田修平, 河原 大輔, 黒橋 禎夫:
  ニューラルネットワークを利用した中国語の統合的な構文解析,

The following paper received the Young Researcher award of the 26-th annual meeting of the association for natural language processing †

• 植田 暢大, 河原 大輔, 黒橋 禎夫:
  BERTとRefinementネットワークによる統合的照応・共参照解析,

We will present the following papers at EMNLP-IJCNLP2019 (2019/11/3-7) †

• Jun Saito, Yugo Murawaki and Sadao Kurohashi:
  Minimally Supervised Learning of Affective Events Using Discourse Relations
• Qianying Liu, Wenyu Guan,Sujian Li and Daisuke Kawahara:
  Tree-structured Decoding for Solving Math Word Problems
• Hirokazu Kiyomaru, Kazumasa Omura, Yugo Murawaki, Daisuke Kawahara and Sadao Kurohashi:
  Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction (COIN 2019)
• Norio Takahashi, Tomohide Shibata, Daisuke Kawahara and Sadao Kurohashi:
  Machine Comprehension Improves Domain-Specific Japanese Predicate-Argument Structure Analysis (MRQA 2019)

Search Engine Infrastructure based on Deep Natural Language Processing †

The essential purpose of information retrieval is not to retrieve just a relevant document but to acquire the information or knowledge in the document. We have been developing a next-generation infrastructure of information retrieval on the basis of the following techniques of deep natural language processing: precise processing based not on words but on predicate-argument structures, identifying the variety of linguistic expressions and providing a bird's-eye view of search results via clustering and interaction.

Machine Translation †

To bring automatic translation by computers to the level of human translation, we have been studying next-generation methodology of machine translation on the basis of text understanding and a large collection of translation examples. We have already accomplished practical translation on the domain of travel conversation, and constructed a translation-aid system that can be used by experts of patent translation.