Semantic decomposition (natural language processing)

Many terms are associated with meaning, including semantics, pragmatics, knowledge and understanding or word sense.

These theories need to be analyzed further to develop an artificial notion of meaning best fit for our current state of knowledge.

[5] Research has so far identified semantic measures and with that word-sense disambiguation (WSD) - the differentiation of meaning of words - as the main problem of language understanding.

[14] Upon this graph marker passing[15][16][17] is used to create the dynamic part of meaning representing thoughts.

Future work uses the created representation of meaning to build heuristics and evaluate them through capability matching and agent planning, chatbots or other applications of natural language understanding.