Semantic tree

A semantic tree is a structure that represents the meanings or senses of words, often used in natural language processing (NLP) to capture the relationships between different meanings of words based on context.

According to Martin Wattenberg, discussing in Martin Wattenberg: ML Visualization and Interpretability, the concept involves finding a correspondence between tree structures in syntax and high-dimensional space. The distances in these trees relate to the meanings and uses of words in different contexts, essentially creating an embedding that highlights semantic differences 1.

In another context, Matt Gardner explains how semantic parsing in NLP has evolved from strict grammar formalisms to more flexible neural models, illustrating efforts to map input text to logical forms that align with tree-structured representations 2.

Thus, a semantic tree is a crucial tool in understanding and processing the complex layers of meaning in language, aiding tasks like word sense disambiguation and semantic parsing.