After decades of massive digitisation, an unprecedented number of historical documents are
available in digital format, along with their machine-readable texts. While this represents a …

An enormous amount of digital information is expressed as natural-language (NL) text that is
not easily processable by computers. Knowledge Graphs (KG) offer a widely used format for …

Abstract The Semantic Web contains an enormous amount of information in the form of
knowledge bases (KB). To make this information available, many question answering (QA) …

Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust
Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive …

Equip** machines with comprehensive knowledge of the world's entities and their
relationships has been a longstanding goal of AI. Over the last decade, large-scale …

Applying natural language processing for mining and intelligent information access to tweets
(a form of microblog) is a challenging, emerging research area. Unlike carefully authored …

We present YAGO, a light-weight and extensible ontology with high coverage and quality.
YAGO builds on entities and relations and currently contains more than 1 million entities and …

Named Entity Recognition seeks to extract substrings within a text that name real-world
objects and to determine their type (for example, whether they refer to persons or …

A significant amount of information about drug-related safety issues such as adverse effects
are published in medical case reports that can only be explored by human readers due to …

During the last decade text mining has become a widely used discipline utilizing statistical
and machine learning methods. We present the tm package which provides a framework for …