NLP and the Representation of Data on the Semantic Web

One of the goals of data scientists and curators is to get information (contained in text) organized and integrated in a way that can be easily consumed by people and machines. A starting point for such a goal is to get a model to represent the information. This model should ease to obtain knowledge semantically (e.g., using reasoners and inferencing rules). In this sense, the Semantic Web is focused on representing the information through the Resource Description Framework (RDF) model, in which the triple (subject, predicate, object) is the basic unit of information. In this context, the natural language processing (NLP) field has been a cornerstone in the identification of elements that can be represented by triples of the Semantic Web. However, existing approaches for the representation of RDF triples from texts use diverse techniques and tasks for such purpose, which complicate the understanding of the process by non-expert users. This chapter aims to discuss the main concepts involved in the representation of the information through the Semantic Web and the NLP fields.