Divide and Translate Legal Text Sentence by Using Its Logical Structure
Bùi Thanh Hùng, Nguyen Le Minh, Akira Shimazu · 2012
Translating legal text is generally considered to be difficult because legal text has some characteristics that make it different from other daily-use documents and legal text is usually long and complicated. In order boost the legal text translation quality, splitting an input sentence becomes mandatory. In this paper, we propose a novel method based on the logical structure of legal text sentence for dividing and translating legal text. We use a statistical learning method-Conditional Random Fields (CRFs) with rich linguistic information to recognize the logical structure of legal text sentence. We adapt the logical structure of legal text sentence to divide the sentence. By doing so, translation quality improves. Our experiments show that our approach can achieve better result for both Japanese-English and English-Japanese legal text translation by BLEU, NIST and TER score.