[01] Huynh Quang Duc, Computer Science Center of Soc Trang Vocational College, Soc Trang Province, Vietnam. [02] Tran Le Tam Linh, Center for Mathematical Science, University of Science, National University, Ho Chi Minh City, Vietnam.

Issue about Semantic Role Labelling (SRL) for bilingual has been studying on many popular languages as English, French, etc. However, Semantic Role Labelling tasks for unpopular languages as Vietnamese are currently limited, especially for making the most of semantic similarities on bilingual English-Vietnamese. In this paper, we propose a solution for Semantic Role Labelling tasks automatically on bilingual English-Vietnamese Corpus in order to take full advantages of the translations of cross-language lexicalization, but it also maintains the core elements of its semantic role. This system has used corpus from the Web to build sets associated with the ability to combine many different meaning words found in the corpus, and it has also used an unsupervised algorithm to label the semantic role in English, which based on semantic similarities through English-Vietnamese corpus. Then, this system will automatically project labels from English to Vietnamese via available links.

Unsupervised, Bilingual, Parallel Corpus, Semantic Role Labelling, Machine Translation

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