Abstract
This paper describes the zNLP system for the BUCC 2017 shared task. Our system identifies parallel sentence pairs in Chinese-English comparable corpora by translating word-by-word Chinese sentences into English, using the search engine Solr to select near-parallel sentences and then by using an SVM classifier to identify true parallel sentences from the previous results. It obtains an F1-score of 45% (resp. 43%) on the test (training) set.
Cite
CITATION STYLE
Zhang, Z., & Zweigenbaum, P. (2017). zNLP: Identifying parallel sentences in Chinese-English comparable corpora. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 51–55). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-2510
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