Assignment 1: Princeton WordNet

Deadline: 23 September, 23.59 CET

How to report the assignment

The completed assignment file assign1.py should be mailed to johan.roxendal@svenska.gu.se, with an appropriate subject line. Remember to write your full names in the mail, and as a header in the assignment file (as a doc string).

Requirements

The assignment is done in groups of two.
It is ok to discuss solutions with students outside of your group, but copying code is the same as cheating (the same goes for the web, of course).
If requested, both members in a group should be able to explain the solution to the assignment.
Always hand in the assignment before the deadline, even if you have not been able to fully complete the assignment.
If the assignment is uncompleted, clearly state what is left to do, and what you need help with.

Description

In this assignment we will work with the Princeton WordNet.

Read NLTK book chapter 2.5 about Princeton WordNet, and test the examples.

Note 1: the focus of this assignment is on the synonymy relation with its corresponding concept synset (Senses and Synonyms in chapter 2.5), but have a look at the other relations also.

Note 2: WordNet is a rich lexical-semantic resource, but don't be overwhelmed by its content, we only use it here to make things more interesting.
Create a file assign1.py containing the code below. (replace NAME with your full names). Define all functions in this file.
```
"""Assignment 1: WordNet (deadline: 2011-09-23)
Name 1: NAME
Name 2: NAME
"""
from nltk.corpus import wordnet as wn
import random
```

Define a function print_synsets(word) that given word returns a string with the following information for every synset it is a member of:

lemma_names
definition
examples (if there is no examples, output no examples)

If word is missing from WordNet, output no synsets.

Hint 1: before you start, think through what needs to be done, and define help functions where appropriate.

Hint 2: you should not use print in the function definition.

Hint 3: use string formatting.

The output of print_synsets is exemplified below.

>>> import assign1

>>> assign1.print_synsets('dog')
'synset 1: {dog, domestic_dog, Canis_familiaris}\n  def: "a member of the genus Canis [...] the rabbit"\n\n'

>>> print assign1.print_synsets('dog')
synset 1: {dog, domestic_dog, Canis_familiaris}
  def: "a member of the genus Canis (probably descended from the common wolf) that has been domesticated by man since prehistoric times; occurs in many breeds"
  example: "the dog barked all night"

synset 2: {frump, dog}
  def: "a dull unattractive unpleasant girl or woman"
  example: "she got a reputation as a frump"
  example: "she's a real dog"

synset 3: {dog}
  def: "informal term for a man"
  example: "you lucky dog"

synset 4: {cad, bounder, blackguard, dog, hound, heel}
  def: "someone who is morally reprehensible"
  example: "you dirty dog"

synset 5: {frank, frankfurter, hotdog, hot_dog, dog, wiener, wienerwurst, weenie}
  def: "a smooth-textured sausage of minced beef or pork usually smoked; often served on a bread roll"
  no examples

synset 6: {pawl, detent, click, dog}
  def: "a hinged catch that fits into a notch of a ratchet to move a wheel forward or prevent it from moving backward"
  no examples

synset 7: {andiron, firedog, dog, dog-iron}
  def: "metal supports for logs in a fireplace"
  example: "the andirons were too hot to touch"

synset 8: {chase, chase_after, trail, tail, tag, give_chase, dog, go_after, track}
  def: "go after with the intent to catch"
  example: "The policeman chased the mugger down the alley"
  example: "the dog chased the rabbit"

>>> print assign1.print_synsets('qrsx')
no synsets

Define a function synonyms(word) that returns a set of lemma_names of the synsets of word.

The output of synonyms is exemplified below.

>>> assign1.synonyms('dog')
set(['go_after', 'chase_after', 'pawl', 'dog', 'wiener', 'tag',
'frankfurter', 'hound', 'click', 'chase', 'andiron', 'hot_dog', 
'tail', 'Canis_familiaris', 'give_chase', 'wienerwurst', 'bounder', 
'domestic_dog', 'track', 'frank', 'trail', 'blackguard', 'weenie', 
'frump', 'firedog', 'detent', 'dog-iron', 'cad', 'heel', 'hotdog'])

>>> assign1.synonyms('computer')
set(['data_processor', 'computing_machine', 'information_processing_system', 
'calculator', 'computing_device', 'estimator', 'electronic_computer', 
'computer', 'figurer', 'reckoner'])
>>> assign1.synonyms('qrsx')
set([])

Define a function random_pick(lst) that randomly selects an element from a list.

Hint: use random.randint in module random. Try out random.randint(1,10) (execute it a couple of times).

The output of random_pick is exemplified below.
```
>>> assign1.random_pick(['a','b','c','d','e'])
'e'

>>> assign1.random_pick(['a','b','c','d','e'])
'b'

>>> assign1.random_pick(['a','b','c','d','e'])
'c'
```
Define a function random_synonym(word) that randomly generate one of the synonyms of word, except word itself, unless it is the only word.

If word is not in WordNet, then the function returns *word* (a star in the beginning and end of word).

Hint: use synonyms and random_pick.
The output of random_synonym is exemplified below.
```
>>> assign1.random_synonym('dog')
'bounder'

assign1.random_synonym('dog')
'go_after'

>>> assign1.random_synonym('dog')
'hound'

>>> assign1.random_synonym('computer')
'computing_machine'

>>> assign1.random_synonym('xqrs')
'*xqrs*'
```

Define a function synonymify(sentence) that apply random_synonym to every word in sentence.

The output of synonymify is exemplified below.

>>> assign1.synonymify('the dog sits in front his computer')
'*the* wienerwurst baby-sit IN front_man *his* estimator'

>>> assign1.synonymify('the dog sits in front his computer')
'*the* frankfurter baby-sit inch front_line *his* calculator'

>>> assign1.synonymify('the dog sits in front his computer')
'*the* go_after sit_around IN look *his* data_processor'

To think about: the output of synonymify is rather strange. Do you have any ideas on how to improve the function so the meaning of sentence is preserved?