def test_Accuracy(self):
correct = 0
total = 0
lesk = Lesk(self.wordNet, self.fsm)
corpus1 = AnnotatedCorpus("../../new-sentences")
corpus2 = AnnotatedCorpus("../../old-sentences")
for i in range(corpus1.sentenceCount()):
sentence1 = corpus1.getSentence(i)
lesk.autoSemantic(sentence1)
sentence2 = corpus2.getSentence(i)
for j in range(sentence1.wordCount()):
total = total + 1
word1 = sentence1.getWord(j)
word2 = sentence2.getWord(j)
if word1.getSemantic() is not None and word1.getSemantic() == word2.getSemantic():
correct = correct + 1
self.assertEqual(549, total)
self.assertEqual(268, correct)
class SentenceDisambiguationCorpusGenerator:
__annotatedCorpus: AnnotatedCorpus
def __init__(self, folder: str, pattern: str):
"""
Constructor for the DisambiguationCorpusGenerator which takes input the data directory and the pattern for the
training files included. The constructor loads the corpus from the given directory including the given files
the given pattern.
PARAMETERS
----------
folder : str
Directory where the sentence files reside.
pattern : str
Pattern of the tree files to be included in the corpus. Use "." for all files.
"""
self.__annotatedCorpus = AnnotatedCorpus(folder, pattern)
def generate(self) -> DisambiguationCorpus:
"""
Creates a morphological disambiguation corpus from the corpus.
RETURNS
-------
DisambiguationCorpus
Created disambiguation corpus.
"""
corpus = DisambiguationCorpus()
for i in range(self.__annotatedCorpus.sentenceCount()):
sentence = self.__annotatedCorpus.getSentence(i)
disambiguationSentence = AnnotatedSentence()
for j in range(sentence.wordCount()):
annotatedWord = sentence.getWord(j)
if isinstance(annotatedWord, AnnotatedWord):
disambiguationSentence.addWord(
DisambiguatedWord(annotatedWord.getName(),
annotatedWord.getParse()))
corpus.addSentence(disambiguationSentence)
return corpus