👉 Dictionaries computing, also known as dictionary-based methods or lexical analysis, is a fundamental step in the process of natural language processing (NLP) and computational linguistics. It involves converting a sequence of text tokens (such as words or subwords) into meaningful units called tokens, which are typically words, parts of words, or character n-grams. This process is crucial for tasks like part-of-speech tagging, named entity recognition, and machine translation. Dictionaries computing algorithms map each token to its corresponding lexical entry, which contains information like part-of-speech tags, word definitions, and syntactic roles. This step helps in standardizing and structuring raw text data, making it easier for subsequent NLP models to process and understand the language. Dictionaries computing can be performed manually or through automated tools, with modern approaches often leveraging large pre-trained language models to generate more accurate and context-aware token representations.
