Next: Word-Sense Disambiguation Up: Introduction Previous: Introduction
In natural language processing (NLP), word sense disambiguation (WSD) is defined as the task of assigning the appropriate meaning (sense) to a given word in a text or discourse. As an example, consider the following three sentences:
Any system that tries to determine the meanings of the three sentences will need to represent somehow three different senses for the verb fall. In the first sentence, the missiles have been launched on Baghdad. In the second sentence, sales will decrease, and in the third the city will surrender early. WordNet 2.0 Miller1995,Fellbaum19981 contains thirty-two different senses for the verb fall as well as twelve different senses for the noun fall. Note also that the first and third sentence belong to the same, military domain, but use the verb fall with two different meanings.
Thus, a WSD system must be able to assign the correct sense of a given word, in these examples, fall, depending on the context in which the word occurs. In the example sentences, these are, respectively, senses 1, 2 and 9, as listed below.
Providing innovative technology to solve this problem will be one of the main challenges in language engineering to access advanced knowledge technology systems.