I am a student in psychology, but I have very little familiarity with linguistics. I am doing working on flexible cognition and memory, and we are developing a task that requires participants to select objects that can be used to satisfy goals, while systematically varying the association with the object and the goal.
Goals are given as 'tasks' that can be expressed as an infinitive, i.e. "To Dig", and participants would then select a noun (from a field of distractors) that could best be used to perform the task, i.e. "Shovel" or "Stick". The latter would be an example of an object that could be used to perform the task, but is not usually associated with the task in the way that a shovel is.
We would like to have some 'objective' measure of semantic relatedness between the goal (verb/infinitive) and the object (noun). Unfortunately, Wordnet and many other online databases of semantic relatedness don't let you get measures of semantic relatedness across different parts of speech.
So, the question: Does anyone know of a toolset that can be used to extract some measure of semantic relatedness between a word pair, i.e. ('Dig', 'Stick'), across parts of speech, while simultaneously allowing me to specify the part of speech associated with each word in the pair? (to stretch the above example, I want to be able to specify that dig is to be understood as a verb, as in 'to dig' not a noun as in 'let's go to the archeological dig')
I am reasonably fluent in python, and I have already set up NLTK on my computer, but for the life of me I can't figure out how to turn it toward this problem. Hopefully the answer is there somewhere, and if so, code examples would be highly appreciated.