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It's because the level of possible word sequences increases, and also the patterns that notify outcomes turn out to be weaker. By weighting words and phrases in the nonlinear, distributed way, this model can "find out" to approximate phrases and not be misled by any unknown values. Its "understanding" of the supplied phrase isn't really as tightly