2. A computer-implemented method, comprising: receiving, at a computing device, a sentence including one or more words; determining, at the computing device, an index set of possible head-modifier dependencies for the sentence, the index set including inner arcs and outer arcs, the inners arcs representing possible head-modifier dependency between words in the sentence separated by a first distance less than or equal to a distance threshold and outer arcs representing possible head-modifier dependency between words in the sentence separated by a second distance greater than the distance threshold; pruning, at the computing device, the index set based on an augmented vine parsing algorithm to obtain a first pruned index set, the first pruned index set including: (i) each specific inner arc when a likelihood that the specific inner arc is appropriate is greater than a first threshold, and (ii) the outer arcs when a likelihood that there exists any possible outer arc that is appropriate is greater than the first threshold; pruning, at the computing device, the first pruned index set based on a second parsing algorithm to obtain a second pruned index set; determining, at the computing device, a most-likely parse for the sentence from the second pruned index set; and outputting, from the computing device, the most-likely parse.
2. A computer-implemented method, comprising: receiving, at a computing device, a sentence including one or more words; determining, at the computing device, an index set of possible head-modifier dependencies for the sentence, the index set including inner arcs and outer arcs, the inners arcs representing possible head-modifier dependency between words in the sentence separated by a first distance less than or equal to a distance threshold and outer arcs representing possible head-modifier dependency between words in the sentence separated by a second distance greater than the distance threshold; pruning, at the computing device, the index set based on an augmented vine parsing algorithm to obtain a first pruned index set, the first pruned index set including: (i) each specific inner arc when a likelihood that the specific inner arc is appropriate is greater than a first threshold, and (ii) the outer arcs when a likelihood that there exists any possible outer arc that is appropriate is greater than the first threshold; pruning, at the computing device, the first pruned index set based on a second parsing algorithm to obtain a second pruned index set; determining, at the computing device, a most-likely parse for the sentence from the second pruned index set; and outputting, from the computing device, the most-likely parse. 7. The method of claim 2 , wherein the first threshold is determined based on the equation: t ∝ ⁡ ( w ) = ∝ max y ∈ Y ⁢ ( y · w ) + ( 1 - α ) ⁢ 1  I  ⁢ ∑ i ∈ I ⁢ ⁢ m ⁡ ( i ) · w where t ∝ (w) is the threshold, ∝ is a model specific parameter having a value between 0 and 1 inclusive, y is a parse tree of a set of parse trees Y, w is a weight vector, i is an index of a set of indices I, and m(i) is a function of argmax yεY:y(i)=1 y·w.