Natural language understanding systems are the most general and complex systems involving natural language processing. Such systems are universal in the sense that they can perform nearly all the tasks of other language-related systems, such as grammar and style checking, information retrieval, automatic translation, natural language interface, extraction of factual data from texts, text generation, and so forth.
For example, automatic translation can be implemented as a text understanding system, which understands the text in the source language and then generates a precise description of the learned information in the target language.
Hence, creation of a text understanding system is the most challenging task for the joint efforts of computational linguistics and artificial intelligence.
To be more precise, the natural language processing module is only one part of such a system. Most activities related to logical reasoning and understanding proper are concentrated in another its part—a reasoning module. These two modules, however, are closely interrelated and they should work in tight cooperation.
The linguistic subsystem is usually bi-directional, i.e., it can both “understand,” or analyze, the input texts or queries, and produce, or generate, another text as the answer. In other words, this subsystem transforms a human utterance into an internal, or semantic, representation comprehensible to the reasoning subsystem, produces a response in its own internal format, and then transforms the response into a textual answer.
In different systems, the reasoning subsystem can be called the knowledge-based reasoning engine, the problem solver, the expert system, or something else, depending on the specific functions of the whole system. Its role in the whole system of natural language understanding is always very important.
Half a century ago, Alan Turing suggested that the principal test of intelligence for a computer would be its ability to conduct an intelligent dialogue, making reasonable solutions, giving advice, or just presenting the relevant information during the conversation.
This great goal has not been achieved thus far, but research in this direction has been conducted over the past 30 years by specialists in artificial intelligence and computational linguistics.
In order to repeat, the full power of linguistic science and the full range of linguistic data and knowledge are necessary to develop what we can call a true language understanding system.