https://medium.com/altitudehq/is-traditional-nlp-dead-05544ae7d756 Open in app Sign up Sign in [ ] Write Sign up Sign in [1] Member-only story Has LLM killed traditional NLP? Thang Do Altitude Thang Do * Follow Published in Altitude * 6 min read * 4 days ago -- Share Natural Language Processing (NLP) has had a relatively long development period. It is often broken down into smaller problems: text classification, Named Entity Recognition (NER), summarization, etc. to solve concrete challenges. For each smaller challenge, we have different small models to solve it, and sometimes, we must prepare large enough training data. For example, to use text classification to detect when a guest asks about check-in time, we need to create a list of similar questions for the intentcheck-inin the following format (using Rasa NLU syntax): nlu: - intent: check_in_time examples: | - When can I check-in? - What time am I allowed to check-in? - Can you tell me the check-in time? - intent: pool examples: | - Is the pool available for guests to use? - Could you let me know if there is a swimming pool here? ... Then put it into the intent classification model to train. With lots of intents, this file becomes bigger, takes more time to train, and when we add new intents or training phrases, we must retrain. With the rise of Large Language Models like ChatGPT, it can tackle NLP problems more easily. With zero-shot prompts, we just need to put the guest's question and list of intents in a prompt without any examples: -- -- Altitude Altitude Published in Altitude 37 Followers *Last published 4 days ago Welcome to our Engineering Blog, our team will detail various components of the solution architecture of Altitude. Altitude is the all in one smart accommodation platform built to simplify the process -- we're providing you the building blocks to succeed. www.altitudehq.com Thang Do Thang Do Follow Written by Thang Do 66 Followers *67 Following Follow No responses yet Help Status About Careers Press Blog Privacy Terms Text to speech Teams