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- paragraph type Paragraph assertion.
- paragraph hasContent "The World Wide Web is nowadays one of the most prominent sources of information and knowledge. De- spite the constantly increasing availability of semi-structured or structured data, a major portion of its content is still represented in an unstructured form, namely free text: deciphering its meaning is a complex task for machines and yet relies on subjective human interpretations. Hence, there is an ever growing need for Intelligent Web-reading Agents, i.e., Artificial Intelligence systems that can read and understand human language in documents across the Web. Ideally, these agents should be robust enough to interchange between heterogeneous sources with agility, while maintaining equivalent reading capabilities. More specifically, given a set of input corpora (where an item corresponds to the textual content of a Web source), they should be able to navigate from corpus to corpus and to extract compa- rable structured assertions out of each one. Ultimately, the collected data would feed a target Knowledge Base (KB), namely a repository that encodes areas of human intelligence into a richly shaped representation. Typically, KBs are composed of graphs, where real-world and abstract entities are bound together through relationships, and classified according to a formal description of the world, i.e., an ontology." assertion.