The NL2KR Platform for building Natural Language Translation Systems

نویسندگان

  • Nguyen Ha Vo
  • Arindam Mitra
  • Chitta Baral
چکیده

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-λ, 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.

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تاریخ انتشار 2015