def train(self, to_exclude, corpus: TextCorpus):
        table = defaultdict(Counter)
        words = NGram(self.STOP_WORD for _ in range(self._ngram_size))

        for text in corpus:
            tagged_text = pos_tag(text)
            for tagged_word in text:
                tag = tagged_word[1]
                word = tagged_word[0]
                if tag in to_exclude:
                    continue
                else:
                    table[tuple(words)][tagged_word] += 1
                    words.popleft()
                    words.append(tagged_word)

        table[tuple(words)][self.STOP_WORD] += 1

        self._table = table
        self._probabilities = {words: ProbabilityTable(counts)
                               for words, counts in table.items()}