Abstract
This paper presents the NL2KR platform to build systems that can translate text to different formal languages. It is freelyavailable1, customizable, and comes with an Interactive GUI support that is useful in the development of a translation system. Our key contribution is a userfriendly system based on an interactive multistage learning algorithm. This effective algorithm employs Inverse-, Generalization and user provided dictionary to learn new meanings of words from sentences and their representations. Using the learned meanings, and the Generalization approach, it is able to translate new sentences. NL2KR is evaluated on two standard corpora, Jobs and GeoQuery and it exhibits state-of-The-Art performance on both of them.
Cite
CITATION STYLE
Vo, N. H., Mitra, A., & Baral, C. (2015). The NL2KR platform for building natural language translation systems. In ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference (Vol. 1, pp. 899–908). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/p15-1087
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