Homework

(1) Manually build a feature set that might predict specific word senses. Start by selecting a word that is highly polysemous (has many senses). You can find such words in regular dictionaries or in WordNet. Suppose you chose the verb "find."
Next you type "find"  "finds", "found" into a search engine and extract sentences that contain two (or more, if you want) senses of this verb. You make two (or more) batches of sentences, one for each sense.
E.g., 
batch one: He finds the course interesting
…
batch two: He found his keys under the bed
…

Then you reflect on what properties might distinguish these two (or more) sense of "find". Write down these properties (features). Remember that they can be any of 
the following: 
--words in the context (bag of words)
--words in the context in specific distance to the target (find)
--context words with specific grammatical relations (subject-of, object-of,…)
--morphology (does one sense occur typically in the past tense? The 3rd person?)

You don't need to write the features down in any formal way.

Then test your feature set by searching the web for more and *different* sentences 
containing the verb "find." See how well your feature sets for each sense really apply to these data and consider whether and how you would change the feature set.

Write a short report on your experiment.