Word sense disambiguation is the task to identify the intended meaning of an ambiguous word in a certain context, one of the central problems in natural language processing. This paper describes four novel supervised disambiguation methods which adapt some familiar algorithms. They built on the Vector Space Model using an automatically generated stop list and two