홈 › Papers

Back to Basics for Monolingual Alignment: Exploiting Word Similarity and Contextual Evidence

We present a simple, easy-to-replicate monolingual aligner that demonstrates state-of-the-art performance while relying on almost no supervision and a very small number of external resources. Based on the hypothesis that words with similar meanings represent potential pairs for alignment if located in similar contexts, we propose a system that operates by finding such pairs. In two intrinsic evaluations on alignment test data, our system achieves F1 scores of 88{--}92{\%}, demonstrating 1{--}3{\%} absolute improvement over the previous best system. Moreover, in two extrinsic evaluations our aligner outperforms existing aligners, and even a naive application of the aligner approaches state-of-the-art performance in each extrinsic task.

Code (0)

등록된 구현이 없습니다.

Tasks

Similar Papers 제목 키워드 기반