Andrés Felipe Puerta Velez

NLP in Practice: From Corpus Linguistics to RAG with Python

Natural language processing offers today a mature set of tools for analyzing textual corpora systematically and reproducibly, but the path from having documents to obtaining results is not always clear. This workshop walks through that path from start to finish. In two hours, participants will build an understanding of the NLP ecosystem: its history, logic, and methods. The session opens with a timeline from the first rule-based models to transformers, followed by a map of techniques organized by problem type (classification, entity extraction, semantic search, generation) so each participant can identify which method they need for a specific textual problem. The second part covers two Python implementations. First, topic modeling with BERTopic, reviewing the internal pipeline of embeddings, UMAP, and HDBSCAN. Second, a conversational assistant with RAG: corpus indexing, semantic retrieval, and connection to a language model to answer queries about the documents. At the end, each participant will have a functional notebook with both pipelines and a clear map of the ecosystem to guide their own textual analysis projects.