How does Chinese NLP work?
- Tokenization. Tokenization in Chinese NLP is the process of segmenting a continuous stream of text into meaningful units, or words. This is particularly challenging in Chinese due to the lack of spaces between characters.
- Part-of-Speech Tagging. Part-of-Speech Tagging assigns grammatical categories to each word in a sentence. In Chinese NLP, this helps in understanding the syntactic structure of sentences.
- Named Entity Recognition. Named Entity Recognition identifies and classifies key entities in a text, such as names of people, organizations, and locations, which is critical for understanding context in Chinese texts.
- Machine Translation. Machine Translation converts text from one language to another, in this case, enabling seamless translation from Chinese to other languages and vice versa using advanced algorithms.