facilitate <term> language acquisition </term> . From this , a <term> language learning model </term>
<term> machine translation systems </term> . This , the first experiment in a series of experiments
texts </term> in the domain of Navy messages . This abstract describes a <term> natural language
annealing approach </term> is used to implement this <term> alignment algorithm </term> . The preliminary
together . Like <term> semantic grammar </term> , this allows easy exploitation of <term> limited
This paper proposes a method for resolving this <term> ambiguity </term> based on <term> statistical
part-of-speech tag sequences </term> . We incorporate this analysis into a <term> diagnostic tool </term>
restricted-domain parsing </term> is proposed . In this approach , the definitions of the <term>
translations </term> of each other . Using this <term> approach </term> , we extract <term> parallel
generalized LR parsing </term> is enhanced in this approach . <term> Parsing </term> proceeds
system </term> has shown great effectiveness of this approach . <term> Word Identification </term>
built and will demonstrate an application of this approach called <term> LCS-Marine </term> .
clustering of word co-occurrences </term> . This approach differs from other approaches
performance </term> . We describe our use of this approach in numerous fielded <term> user
forms </term> instead of <term> words </term> . This approach is sufficient for languages with
highly accurate one . Experiments show that this approach is superior to a single <term> decision-tree
operational semantics </term> . The value of this approach is that as the <term> operational
derivations </term> . The principle advantage of this approach is that knowledge concerning translation
successive learners </term> is presented . This approach only requires a few <term> common
representation </term> . After introducing this approach to <term> MT system </term> design
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