Which component of NLP focuses on understanding the meaning of words in context?

The choice related to understanding the meaning of words in context is semantic analysis. This component of Natural Language Processing (NLP) deals with interpreting and extracting meaning from text by examining the context in which words appear. By analyzing relationships between words, phrases, and sentences, semantic analysis strives to capture nuances such as meaning variations, connotations, and the relationships between different terms.

In contrast, tokenization breaks down text into individual units like words or phrases, allowing for easier processing but does not inherently consider the context or meaning. Part-of-speech tagging assigns parts of speech to individual words but also does not address the semantic understanding necessary for grasping meaning in context. Question answering systems may leverage semantic analysis as part of their functionality, but they themselves are broader applications that utilize various NLP methods to formulate answers to queries rather than focusing specifically on understanding meaning in context.