TIB Leibniz Information Centre for Science and Technology
Jennifer D’Souza is a Postdoctoral Researcher at the TIB Leibniz Information Centre for Science and Technology in the R&D Department. Her research interests mainly include developing supervised machine learning techniques for natural language processing to facilitate text mining and automated information extraction. Her current primary research theme is knowledge graph construction from scientific text by NLP methods. Aside from which, she is also interested in scientometrics.
Talks and Events
2022 Talk: The State Of The Art On Knowledge Graph Construction From Text
Knowledge graphs (KG) play a crucial role in many modern applications. The industrial knowledge is scattered in large volumes of both structured and unstructured data sources and bringing them to a unified knowledge graph can bring a lot of value. However, automatically constructing a KG from natural language text is challenging due to the ambiguity and impreciseness of the natural languages. Recently, many approaches have been proposed to transform natural language text into triples to construct KGs. This presentation aims to summarize the research progress over the KG construction from text with a specific focus on the information acquisition branch entailing entity and relation extraction covering the state of the art methods and tools. In this talk, we will provide an overview of the field of knowledge graph construction from text including the state of the art methods, techniques and tools for constructing knowledge graphs from text, their capabilities, limitations and current challenges. This will be useful for any practitioner who is interested in building knowledge graphs for their organizations.