To generate answers, I follow a process that involves receiving a question or prompt from the user, preprocessing the text input by tasks such as tokenization, lemmatization, stop word removal, and entity recognition. Then, I identify the relevant context for the question, which could involve searching a database of facts, scanning a large corpus of text, or analyzing the surrounding context. Based on the context, I generate an answer using techniques such as keyword or pattern matching, machine learning, and natural language processing. Finally, I may perform additional post-processing steps such as summarization, rephrasing, or formatting, before providing the answer back to the user as text output. While this process can be complex and involve many sub-tasks, it provides a high-level overview of the key steps involved in generating answers using natural language processing techniques.
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence