resources </term> are <term> monolingual </term> . We also refer to an <term> evaluation method </term>
approximations </term> for these computations . We also discuss some practical ways of dealing
given biased <term> gold standard </term> it also enables <term> automatic parameter optimization
indicators for the top-level prediction task . We also find that the <term> transcription errors
evaluate their relative performances . We also introduce a new strategy , called <term>
96 % and a <term> recall </term> of 98 % . It also gets a <term> precision </term> of 70 % and
</term> of <term> abstract moves </term> . We also present a prototype <term> concordancer </term>
different <term> inference types </term> . The paper also discusses how <term> memory </term> is structured
can make a fair copy of not only texts but also graphs and tables indispensable to our
and the <term> typing location </term> can be also changed in lateral or longitudinal directions
aspects of <term> language learning </term> are also discussed . Current <term> natural language
appear cooperative or graceful unless they also incorporate numerous <term> non-literal aspects
vital to <term> machine translation </term> are also discussed together with various interesting
view of <term> language definition </term> are also noted . Representative samples from an <term>
conversational vehicle to deliver it . The paper also promotes a new view for <term> extensional
way . This <term> generation system </term> also uses <term> disjunctive feature structures
interface </term> for browsing and editing was also designed and implemented . The principle
training corpus </term> and the real tasks are also taken into consideration by enlarging the
<term> sentence </term> again . This method is also capable of handling <term> unknown words </term>
field of <term> speech processing </term> , but also in the related areas of <term> Human-Machine
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