Explores methods for information extraction, including traditional and embedding-based approaches, supervised learning, distant supervision, and taxonomy induction.
Introduces Natural Language Processing (NLP) and its applications, covering tokenization, machine learning, sentiment analysis, and Swiss NLP applications.
Explores coreference resolution models, challenges in scoring spans, graph refinement techniques, state-of-the-art results, and the impact of pretrained Transformers.
