I need a small working prototype that automatically tags English text with the three key parts of speech I care about—nouns, verbs and adjectives. All input will be fairly formal (think articles, reports, manuals rather than tweets), so accuracy on well-structured sentences matters more than handling slang. You are free to choose the most suitable NLP stack—spaCy, NLTK, a lightweight Transformer model, or your own custom pipeline—as long as the final code is clear, documented and easy for me to run locally. A concise README that explains environment setup, a short sample text, and the expected tagged output will complete the hand-off. Once the core tagging works reliably on a handful of representative documents, we can discuss any next steps such as expanding to more parts of speech or wrapping the logic in an API, but for now the goal is a clean, focused prototype that highlights nouns, verbs and adjectives with high precision on formal English prose. P.S: Please bid if you think yourself is Native English It is short-term task for making prototype, but has potential to extend this task!!