Automatic extraction and identification of argumentative structures from natural language text, including premises, conclusions, argument schemes, and relationships between main and subsidiary arguments or main and counter-arguments within discourse.

• Natural Language Processing
• Computer Science
• Artificial Intelligence
• Cognitive Science
• Human-Computer Interaction
• Information Retrieval
• Machine Learning
• Text Mining
• Discourse Analysis

A machine learning model is trained on a dataset of news articles to identify the arguments presented in each article, such as the claim and evidence provided to support it. The model can then be used to analyze other texts, such as political speeches or legal documents, to identify their argumentative structures.

• Managing and evolving the semantic data model