Python multiprocesing and NLTK wordnet path similarity
It is very likely that the module in separate processes attempts to access the very same file with Wordnet data. This would result in dependence on GIL to access the file or OS-level file locks use. Both cases would explain the behaviour you are observing.
I am using multiprocessing pool to speed up the title extraction process on a text corpus. At one stage of the code, I am using wordnet path similarity module to determine the similarity of two words. 
If i run my code sequentially i.e. without the use of multiprocessing pool, I get normal times in calculating this path similarity. However, when I use multiprocessing to process multiple documents simultaneously, I observe great time delays in computing this path similarity as compared to sequential.
Question: Does NLTK show any problems with multiprocessing module ?