Entity & Information Extraction

This lecture covers the process of extracting knowledge from text documents, focusing on key concepts such as knowledge modeling, automated creation of knowledge bases, keyphrase extraction, named entity recognition, and knowledge inference. The instructor discusses the challenges and objectives of information extraction, as well as the use of probabilistic models and algorithms like the Viterbi algorithm. Various approaches to information extraction, including supervised machine learning and distant supervision, are also explored.