How does Danish NLP work?
- Tokenization. Tokenization involves breaking down text into smaller components called tokens, which can be words or phrases, to facilitate further analysis.
- Part-of-Speech Tagging. This technique assigns parts of speech to each token, helping to understand the grammatical structure and meaning of sentences.
- Named Entity Recognition. Named Entity Recognition (NER) identifies and categorizes key entities in text such as names, organizations, and locations, which is essential for understanding context.
- Sentiment Analysis. Sentiment analysis evaluates text to determine the emotional tone behind it, often used in opinion mining and customer feedback analysis.