19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature.
19. The method of claim 5 , wherein the at least one feature includes at least one of a set of features, including: a parse-tree-word-level confidence score calculated based on respective word-level confidence scores of a plurality of words of the respective sub-tree and/or its surrounding sub-trees; a POS-tag confidence score based on respective POS-tag scores computed for the POS tag assignments of the plurality of words of the respective sub-tree and/or its surrounding sub-trees; a linking score representing a conditional probability of a link of a highest level of the respective sub-tree, the link including a dependency relation and a directionality; a linking score representing a conditional probability of a link of a highest level of the surrounding sub-trees, the link including a dependency relation and a directionality; a history score which includes, for each of at least one child sub-tree of the surrounding sub-trees, the surrounding child sub-trees' previously computed confidence score; each of a plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of the plurality of POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the respective sub-tree's corresponding section of the interpreted text; each of a plurality of multi-level hierarchical POS tags corresponding to the plurality of words of the surrounding sub-trees' corresponding section of the interpreted text; a dependency relation characteristic; a single level joint head and dependency relation (SL-JHD) characteristic; a single level joint mod and dependency relation (SL-JMD) characteristic; a single level joint head, mod, and dependency relation (SL-JHMD) characteristic; a joint dependency relation (JDR) characteristic; a multi-level joint head and dependency relation (ML-JHD) characteristic; a multi-level joint mod and dependency relation (ML-JMD) characteristic; a multi-level joint head, mod, and dependency relation (ML-JHMD) characteristic; a head, dependency, and left and right neighbors (HDLRN) characteristic; a sub-tree size characteristic; and a semantic slot feature. 20. The method of claim 19 , wherein the at least one feature includes a combination of at least two of the set of features in addition to the at least one of the set.