What are the best algorithms for Word-Sense-Disambiguation
Well, WSD is an open problem (since it's language... and AI...), so currently each of those claims are in some sense valid.  If you are engaged in a domain-specific project, I think you'd be best served by a statistical method (Support Vector Machines) if you can find a proper corpus.  Personally, if you're using python, unless you're attempting to do some significant original research, I think you should just use the NLTK module to accomplish whatever you're trying to do.
What are the best algorithms for Word-Sense-Disambiguation
I read a lot of posts, and each one proves in a research document that a specific algorithm is the best, this is very confusing.
I just come up with 2 realizations 1-Lesk Algorithm is deprecated, 2-Adapted Lesk is good but not the best
Please if anybody based on his (Experience) know any other good algorithm that give accuracy up to say 70% or more please mention it . and if there's a link to any Pseudo Code for the algorithm it'll be great, I'll try to implement it in Python or Java .