We present a novel approach to relation extraction that integrates information across documents, performs global inference and requires no labelled text. In particular, we tackle ...
A major source of information (often the most crucial and informative part) in scholarly articles from scientific journals, proceedings and books are the figures that directly pro...
Amr Ahmed, Eric P. Xing, William W. Cohen, Robert ...
Background: Information extraction (IE) efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where import...
Lawrence Hunter, Zhiyong Lu, James Firby, William ...
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...
In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple ent...
Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang...