| Approach Overview | In order to generate such features, much NLP work has to be done beforehand, such as tweet normalization, POS tagging, word stemming, and syntactic parsing . |
| Approach Overview | For syntactic parsing we use a Maximum Spanning Tree dependency parser (McDonald et al., 2005). |
| Introduction | For instance, in the second example, using syntactic parsing , we know that “Windows 7” is connected to “better” by a copula, while “Vista” is connected to “better” by a preposition. |
| Target-dependent Sentiment Classification | In this paper, we rely on the syntactic parse tree to satisfy this need. |
| Abstract | This paper describes a novel technique for incorporating syntactic knowledge into phrase-based machine translation through incremental syntactic parsing . |
| Introduction | Syntactic parsing may help produce more grammatical output by better modeling structural relationships and long-distance dependencies. |
| Introduction | We directly integrate incremental syntactic parsing into phrase-based translation. |