Improving part-of-speech tagging via multi-task learning and character-level word representations

Autor: Anastasyev, Daniil, Gusev, Ilya, Indenbom, Eugene

Publikováno v: Computational Linguistics and Intellectual Technologies, Papers from the Annual International Conference "Dialogue" (2018) Issue 17, 14-27

In this paper, we explore the ways to improve POS-tagging using various types of auxiliary losses and different word representations. As a baseline, we utilized a BiLSTM tagger, which is able to achieve state-of-the-art results on the sequence labell

Externí odkaz: http://arxiv.org/abs/1807.00818