I need an experienced natural-language engineer to give me a clear, working starting point for my upcoming NLP initiative. To keep the first phase lean, I’m looking for: • A concise technical blueprint outlining the recommended pipeline (data ingestion, pre-processing, model choice, and evaluation approach). • A small, reproducible Python notebook that shows the core logic in action on a sample dataset. • A brief README explaining how to run the notebook and adapt the code to new text sources. Feel free to rely on familiar open-source libraries such as spaCy, Hugging Face Transformers, NLTK, or similar—whichever you believe best fits a lightweight proof of concept. Success for this phase means I can clone the repository, install the requirements, run the notebook, and see clean, annotated output that proves the pipeline works end-to-end. If your solution is solid, there will be room for further collaboration as the project evolves.