soynlp

Why we included this project

soynlp is a good fit when you need Korean NLP but don't have labeled data. It learns from the text you give it: point the noun and word extractors at a set of documents and they pick out recurring tokens from statistical regularities, no pretrained models or annotations required. The package also covers tokenization and part-of-speech tagging, all in pure Python over numpy and scikit-learn, so setup stays simple whether you are prototyping or running a batch pipeline. Unsupervised extraction works best when the input documents share vocabulary, which is why the project's own guide advises feeding it a focused, same-domain corpus like movie reviews or a day's worth of news articles. Within that scope it is a practical, lightweight addition to a Korean NLP toolkit.