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. Introduction ~ Computational
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of second language ( L2 ) input
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analysis in a way which supports
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. 5.1 The nature of the lexicon
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of machine learning to meaning
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, the alignment data computed
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detection and 87 % on semantic
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on a held-out test data set .
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e.g. , the activity , a separate
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module can determine the most
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computationally for robust parsing and
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. L2 is interpreted as interlangnage
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structure 2 . ~ Principles el '
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In the previous paragraph we
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system includes facilities for
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and on-line feedback . Syntactic
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solving program comprehension and
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problems in the domain of data
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account of other relevant factors in
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, in addition to error-tags .
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performing error detection and
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on top of the linguistic analysis
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material . Just as important as the
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itself then is understanding
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concerned with robust parsing and
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based on such lexical entries
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violated . ( 3 ) In a multiple
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a category common to most of
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produce detailed morphological
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and generates statistics at different
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object-level errors which facilitates the
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process . The rest of this paper
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with the design of a universal
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for natural language sentences
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system for robust parsing and
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of lexical transfer errors needs
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construct meaning from those words .
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occur frequently and options
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problems that were analyzed are all
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problems , but each problem involves
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