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Question Classification is the process of determining the type of question asked, which helps the QA system to identify the kind of answer that is being sought.

Answer Extraction is the stage in QA systems where the system extracts potential answers from the retrieved documents based on the question’s focus.

Answer Validation is the process in which a QA system verifies the correctness of the extracted answers before presenting them to the user.

Dialogue Management is a component of interactive QA systems that handles the flow of conversation, maintains context, and manages user interaction to clarify and refine questions or answers.

NLP is a field of computer science focused on the interaction between computers and human language. In QA systems, it enables the interpretation and understanding of human language queries.

A Language Model in a QA system predicts the probability distribution of language to generate human-like text and can assist in understanding and generating answers.

Machine Learning in QA systems refers to algorithms that can learn from data to improve the process of question classification, information retrieval, and answer extraction.

A Knowledge Base in a QA system is a structured source of knowledge, such as a database or ontology, that the system queries to find answers.

Semantic Parsing is the process of mapping a natural language question to a logical form that a computer can understand and use to retrieve answers from a structured knowledge source.