Natural Language Processing with Python

Exercises

1. ○ Define a string s = 'colorless'. Write a Python statement that changes this to “colourless” using only the slice and concatenation operations.

2. ○ We can use the slice notation to remove morphological endings on words. For example, 'dogs'[:-1] removes the last character of dogs, leaving dog. Use slice notation to remove the affixes from these words (we’ve inserted a hyphen to indicate the affix boundary, but omit this from your strings): dish-es, run-ning, nation-ality, un-do, pre-heat.

3. ○ We saw how we can generate an IndexError by indexing beyond the end of a string. Is it possible to construct an index that goes too far to the left, before the start of the string?

4. ○ We can specify a “step” size for the slice. The following returns every second character within the slice: monty[6:11:2]. It also works in the reverse direction: monty[10:5:-2]. Try these for yourself, and then experiment with different step values.

5. ○ What happens if you ask the interpreter to evaluate monty[::-1]? Explain why this is a reasonable result.

6. ○ Describe the class of strings matched by the following regular expressions:

   1. [a-zA-Z]+

   2. [A-Z][a-z]*

   3. p[aeiou]{,2}t

   4. \d+(\.\d+)?

   5. ([^aeiou][aeiou][^aeiou])*

   6. \w+|[^\w\s]+

   Test your answers using nltk.re_show().

7. ○ Write regular expressions to match the following classes of strings:

   1. A single determiner (assume that a, an, and the are the only determiners)

   2. An arithmetic expression using integers, addition, and multiplication, such as 2*3+8

8. ○ Write a utility function that takes ...