Natural language understanding concerns with process of comprehending and using languages once the words are recognized. The objective is to specify a computational model that matches with humans in linguistic tasks such as reading, writing, hearing, and speaking. To develop a natural language understanding model, it is required to use knowledge from many disciplines including Linguistics, psycholinguistics, philosophy, and computational linguistics. It is necessary to understand how language works, combine all the approaches to produce complex theories and realize such complex theories as computer programs. Testing of these programs will give a clue as to which of the cases fail so that the programs can be improved. By doing this process repeatedly we can finally get to know how human language processing occurs.
Representing and Understanding
Computing the representation of the meaning of the texts is the most important component. For this purpose it is necessary to define the notion of representation otherwise ambiguity will be become great impediment. A more precise language is required to represent meaning. The representation languages should have the following properties. The representation must be precise and unambiguous and it should capture the intuitive structure of the natural language sentences. Making judgments on grammaticality is not a goal in language understanding. A robust system should be able to understand even a sentence with some mistakes. Syntactic structure indicates the way the words in the sentence are related to each other. Syntactic representations of the languages are usually based on the notion of context-free grammars. Syntactic representation represents sentence structure in terms of what phrases are subparts of other phrases usually in a tree form. These structures give details on structure of the phrases and parts of speech for each word.
Logical form refers to the representation of the context-independent meaning of a sentence. The logical form encodes the possible word senses and identifies the semantic relationships between words and phrases. An abstract set of semantic relationships between the verb and its noun phrases is used to capture these relationships. Once semantic relationships are determined, some word senses may be impossible and thus eliminated from consideration. One of the key tasks in semantic interpretation is to consider what combinations of the individual word meanings can combine to create coherent sentence meanings. Exploiting such interconnections between word meanings can greatly reduce the number of possible word senses for each word in a given sentence.
The Final Meaning Representation
Natural language understanding system uses general knowledge representation to represent and reason about its application domain. The final representation is the language in which all the knowledge based on the application is represented. The goal of contextual interpretation is to take a representation of the structure of a sentence and its logical form, and to map this into some expression in the knowledge representation that allows the system to perform the appropriate task in the domain. One of the final representation language is the first-order predicate calculus.