drawing on finite-state cascades method, its shallow parsing module recognizes named entities in the texts. so that it greatly eases the burden of the deep analysis module.
其浅层句法分析部分采用有限状态层叠的方法,将文本中的命名实体识别出来,从而大大减轻了深层分析部分的负担。
in this paper, a shallow parsing information based approach is proposed to extract translation examples.
本文采用基于浅层句法分析的方法进行翻译实例的获取。
in order to reduce the difficulty of complete syntactic parsing, 「divided-and-conquer」is proposed and shallow parsing is processed.
为了降低完全句法分析的难度,研究人员提出了「分而治之」的策略,进行浅层分析也就是组块分析。
the experiments have proved that the algorithm gives a high accuracy for shallow parsing of real chinese texts with robustness.
实验证明,该方法能够有效地处理真实文本中的浅层分析问题,具有较好的準确率和鲁棒性。