Based on the NT clause theory, this paper carried out the NT clause identification task of punctuation sentences and explored the application effect of the language model in this task. Furthermore, it divided this task into single NT clause identification and sequential NT clauses identification task. In the single NT clause identification task, this paper formalized it into a machine reading comprehension task. From the results, it obtained the accuracy rate of 83.46% on the Fortress Besieged corpus, and reached the accuracy rate of 91.21% in the fish encyclopedia corpus. In the sequential NT clauses identification task, using the single NT model, it fed the punctuation sentences sequence in a pipelined manner and got the sequential NT clauses. The accuracy rate in fish encyclopedia corpus reached 82.03%. The experimental results show that the proposed method can effectively improve the accuracy of Chinese NT clause identification.

[2021-02-05] Printed Article /doc/2019.12.0670/v2