This is because the only explicit dependency range is ( " n " " 1 ) tokens for an " n "-gram model, and since natural languages incorporate many cases of unbounded dependencies ( such as wh-movement ), this means that an " n "-gram model cannot in principle distinguish unbounded dependencies from noise ( since long range correlations drop exponentially with distance for any Markov model ).
2.
This is because the only explicit dependency range is ( " n " " 1 ) tokens for an " n "-gram model, and since natural languages incorporate many cases of unbounded dependencies ( such as wh-movement ), this means that an " n "-gram model cannot in principle distinguish unbounded dependencies from noise ( since long range correlations drop exponentially with distance for any Markov model ).
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