[4Xin1] Poster session 2

[4Xin1-03] Named entity recognition for corporate names in news text data and identification of the name by characteristics of neighboring words

〇Koutarou Tamura¹, Akira Kitauchi², Atsushi Takayama^1,2 (1.Uzabase,Inc., 2.NewsPicks, Inc.)

Keywords:Natural Language Processing, Named-entity recognition, AI

We used huge news data distributed by SPEEDA service, which include not only news on general interest but also business and industry-specific topics, and built a model to extract corporate information appearing in the text as named entity. In this study, we proposed a method to extract the corporate names in the text after segmented by tokenizers and the extracted were matched with a corporate name dictionary added with their automatically-generated abbreviations and so on. Thereby, we succeed in extracting a named entity which is identified as a corporate name and the method improved the accuracy of the task of extracting corporate names and identification of the company.