Lemmatize all Units in self.unit_list.

        Modifies:
            - self.unit_list: converts the .text property into its lemmatized form.

        This method lemmatizes all inflected variants of permissible words to
        those words' respective canonical forms. This is done to ensure that
        each instance of a permissible word will correspond to a term vector with
        which semantic relatedness to other words' term vectors can be computed.
        (Term vectors were derived from a corpus in which inflected words were
        similarly lemmatized, meaning that , e.g., 'dogs' will not have a term
        vector to use for semantic relatedness computation.)

def lemmatize(self):
        """Lemmatize all Units in self.unit_list.

        Modifies:
            - self.unit_list: converts the .text property into its lemmatized form.

        This method lemmatizes all inflected variants of permissible words to
        those words' respective canonical forms. This is done to ensure that
        each instance of a permissible word will correspond to a term vector with
        which semantic relatedness to other words' term vectors can be computed.
        (Term vectors were derived from a corpus in which inflected words were
        similarly lemmatized, meaning that , e.g., 'dogs' will not have a term
        vector to use for semantic relatedness computation.)
        """
        for unit in self.unit_list:
            if lemmatizer.lemmatize(unit.text) in self.lemmas:
                    unit.text = lemmatizer.lemmatize(unit.text)