Extracting knowledge from unstructured text is a long-standing goal of NLP. Although learning approaches to many of its subtasks have been developed (e.g., parsing, taxonomy induc...
This paper describes an incremental parser and an unsupervised learning algorithm for inducing this parser from plain text. The parser uses a representation for syntactic structur...
We reveal a previously unnoticed connection between dependency parsing and statistical machine translation (SMT), by formulating the dependency parsing task as a problem of word a...
We implement a Korean syntactic analyzer which decreases many ambiguities in syntax parse trees using segmentation and semantic connection units. We use dependency grammar for par...
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...