The most frequently used words in English are highly ambiguous; for example, Webster’s Ninth New Collegiate Dictionary lists 94 meanings for the word “run” as a verb alone. Yet people rarely notice this ambiguity. Solving this puzzle has commanded the efforts of cognitive scientists for many years. The solution most often identified is “context”: we use the context of utterance to determine the proper meanings of words and sentences.
The problem then becomes specifying the nature of context and how it interacts with the rest of an understanding system. The difficulty becomes especially apparent in the attempt to write a computer program to understand natural language. Lexical ambiguity resolution (LAR), then, is one of the central problems in natural language and computational semantics research.
It can be said that this ambiguation can be foud in every language. English language for example has a big quantity of wrds each oone with a more than one meaning. Sometimes if the context of what we are reading is not very clear, it can cause us doubts on what is the writer trying to tell us, that’s why experiments are being made in order to find the system which will help us not find these difficulties i the future or the reason why this lexical ambiguity exists.
References:
- Lexical Ambiguity Resolution: Perspective from Psycholinguistics, Neuropsychology and Artificial Intelligence (Hardcover) Retrieved 19:25 May 7 2009, from http://www.amazon.com/Lexical-Ambiguity-Resolution-Psycholinguistics-Neuropsychology/dp/0934613508
- The Lexical Nature of Syntactic Ambiguity Resolution Retrieved 19:30 May 7th 2009, from http://www.ncbi.nlm.nih.gov/pubmed/7984711
