While the average performance of statistical parsers gradually improves, they still attach to many sentences annotations of rather low quality. The number of such sentences grows ...
We develop the syntactic topic model (STM), a nonparametric Bayesian model of parsed documents. The STM generates words that are both thematically and syntactically constrained, w...
Objective: To introduce the availability of grant-to-article linkage data associated with NIH grants and to perform a high-level analysis of the publication outputs and impacts as...
We employ Maximum Entropy model to conduct sub-tree alignment between bilingual phrasal structure trees. Various lexical and structural knowledge is explored to measure the syntac...
We show how web mark-up can be used to improve unsupervised dependency parsing. Starting from raw bracketings of four common HTML tags (anchors, bold, italics and underlines), we ...
Valentin I. Spitkovsky, Daniel Jurafsky, Hiyan Als...