The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

Automated relation extraction (RE) from biomedical literature is critical for many downstream
text mining applications in both research and real-world settings. However, most existing …

Organized relational knowledge in the form of “knowledge graphs” is important for many
applications. However, the ability to populate knowledge bases with facts automatically …

We introduce the brat rapid annotation tool (BRAT), an intuitive web-based tool for text
annotation supported by Natural Language Processing (NLP) technology. BRAT has been …

Past work in relation extraction has focused on binary relations in single sentences. Recent
NLP inroads in high-value domains have sparked interest in the more general setting of …

In response to the continuing research interest in computational semantic analysis, we have
proposed a new task for SemEval-2010: multi-way classification of mutually exclusive …

Please note that this manual describes the original Stanford Dependencies representation.
As of version 3.5. 2, the default representation output by the Stanford Parser and Stanford …

Sequence labeling for extraction of medical events and their attributes from unstructured text
in Electronic Health Record (EHR) notes is a key step towards semantic understanding of …

Motivation: Despite the central role of diseases in biomedical research, there have been
much fewer attempts to automatically determine which diseases are mentioned in a text …

This paper details the coreference resolution system submitted by Stanford at the CoNLL-
2011 shared task. Our system is a collection of deterministic coreference resolution models …