Third Approach: Dependency Trees

Abstract

After exploring several approaches and representational structures in the previous two chapters, we found that the formalism that best suits our needs is the dependency tree representation. Thus, in this chapter, we present a parser that is based on a dependency tree. This parser’s algorithm uses heuristic rules to infer dependency relationships between words, and it uses word co-occurrence statistics (which are learned in an unsupervised manner) to resolve ambiguities such as PP attachments. If a complete parse cannot be produced, a partial structure is built with some (if not all) dependency relations identified.