コード例 #1
0
    def get_parent(synset: Synset):
        """
        Returns one of the parents of the synset.
        :param synset: The synset to obtain the parent from
        :return: One of the parents of the synset
        """

        return random.choice(synset.hypernyms())
コード例 #2
0
ファイル: lexicon.py プロジェクト: blacklabai/Imagyn
    def get_parents(synset: Synset):
        """
        Returns all parents of the synset (hypernyms).
        :param synset: The synset to obtain the parent from
        :return: List of the parents of the synset
        """

        return synset.hypernyms()
コード例 #3
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    def get_grandparents(synset: Synset):
        """
        Returns all grandparents of the synset.
        :param synset: The synset to obtain the grandparents from
        :return: The grandparents of the synset
        """

        grandparents = []

        for parent in synset.hypernyms():
            grandparents.extend(parent.hypernyms())

        return grandparents
コード例 #4
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ファイル: wordnet.py プロジェクト: Trixter9994/lazero
    def lowest_common_hypernyms(self,
                                synset,
                                other,
                                simulate_root=False,
                                use_min_depth=False):
        '''
        -- NOTE: THIS CODE IS COPIED FROM NLTK3 --
        Get a list of lowest synset(s) that both synsets have as a hypernym.
        When `use_min_depth == False` this means that the synset which
        appears as a hypernym of both `self` and `other` with the lowest
        maximum depth is returned or if there are multiple such synsets at
        the same depth they are all returned

        However, if `use_min_depth == True` then the synset(s) which has/have
        the lowest minimum depth and appear(s) in both paths is/are returned.

        By setting the use_min_depth flag to True, the behavior of NLTK2 can
        be preserved. This was changed in NLTK3 to give more accurate results
        in a small set of cases, generally with synsets concerning people.
        (eg: 'chef.n.01', 'fireman.n.01', etc.)

        This method is an implementation of Ted Pedersen's "Lowest Common
        Subsumer" method from the Perl Wordnet module. It can return either
        "self" or "other" if they are a hypernym of the other.

        :type other: Synset
        :param other: other input synset
        :type simulate_root: bool
        :param simulate_root: The various verb taxonomies do not
            share a single root which disallows this metric from working for
            synsets that are not connected. This flag (False by default)
            creates a fake root that connects all the taxonomies. Set it
            to True to enable this behavior. For the noun taxonomy,
            there is usually a default root except for WordNet version 1.6.
            If you are using wordnet 1.6, a fake root will need to be added
            for nouns as well.
        :type use_min_depth: bool
        :param use_min_depth: This setting mimics older (v2) behavior of NLTK
            wordnet. If True, will use the min_depth function to calculate
            the lowest common hypernyms. This is known to give strange
            results for some synset pairs (eg: 'chef.n.01', 'fireman.n.01')
            but is retained for backwards compatibility
        :return: The synsets that are the lowest common hypernyms of both
            synsets
        '''

        fake_synset = Synset(None)
        fake_synset._name = '*ROOT*'
        fake_synset.hypernyms = lambda: []
        fake_synset.instance_hypernyms = lambda: []

        if simulate_root:
            self_hypernyms = chain(synset._iter_hypernym_lists(),
                                   [[fake_synset]])
            other_hypernyms = chain(other._iter_hypernym_lists(),
                                    [[fake_synset]])
        else:
            self_hypernyms = synset._iter_hypernym_lists()
            other_hypernyms = other._iter_hypernym_lists()

        synsets = set(s for synsets in self_hypernyms for s in synsets)
        others = set(s for synsets in other_hypernyms for s in synsets)
        if self.core_taxonomy is not None:
            synsets.intersection_update(
                map(lambda syn: wordnet.synset(syn), self.known_concepts))
            others.intersection_update(
                map(lambda syn: wordnet.synset(syn), self.known_concepts))
        synsets.intersection_update(others)

        try:
            if use_min_depth:
                max_depth = max(s.min_depth() for s in synsets)
                unsorted_lch = [
                    s for s in synsets if s.min_depth() == max_depth
                ]
            else:
                max_depth = max(s.max_depth() for s in synsets)
                unsorted_lch = [
                    s for s in synsets if s.max_depth() == max_depth
                ]
            return sorted(unsorted_lch)
        except ValueError:
            return []