Natural Language Processing with Python

Exercises

1. ○ Search the Web for “spoof newspaper headlines,” to find such gems as: British Left Waffles on Falkland Islands, and Juvenile Court to Try Shooting Defendant. Manually tag these headlines to see whether knowledge of the part-of-speech tags removes the ambiguity.

2. ○ Working with someone else, take turns picking a word that can be either a noun or a verb (e.g., contest); the opponent has to predict which one is likely to be the most frequent in the Brown Corpus. Check the opponent’s prediction, and tally the score over several turns.

3. ○ Tokenize and tag the following sentence: They wind back the clock, while we chase after the wind. What different pronunciations and parts-of-speech are involved?

4. ○ Review the mappings in Table 5-4. Discuss any other examples of mappings you can think of. What type of information do they map from and to?

5. ○ Using the Python interpreter in interactive mode, experiment with the dictionary examples in this chapter. Create a dictionary d, and add some entries. What happens whether you try to access a non-existent entry, e.g., d['xyz']?

6. ○ Try deleting an element from a dictionary d, using the syntax del d['abc']. Check that the item was deleted.

7. ○ Create two dictionaries, d1 and d2, and add some entries to each. Now issue the command d1.update(d2). What did this do? What might it be useful for?

8. ○ Create a dictionary e, to represent a single lexical entry for some word of your choice. Define keys such as headword, part-of-speech, sense, and example, and ...