Now that you have learnt the building block of semantic processing ,let’s learn to solve a common problem in semantic analysis -word sense disambiguation.
Word sense disambiguation(WSD) is the task of identifying the correct sense of an ambiguous word such as ‘bank’, ‘bank’, ‘pitch’ etc.
In the following lecture, let’s understand the various techniques used for word sense disambiguation.
Supervised techniques for word sense disambiguation require the input words to be tagged with their senses. the sense is the label assigned to the word. in unsupervised techniques , words are not tagged with their sense, which are to be inferred using other techniques.
Let’s talk about supervised techniques first. one simplest text classification algorithms is the Naive Bayes Classifier.
In the next lecture, let’s learn about the unsupervised technique.