How to use the depccg.tree.Tree.make_unary function in depccg

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github masashi-y / depccg / depccg / tools / reader.py View on Github external
def rec(node):
            attrib = node.attrib
            if 'terminal' not in attrib:
                cat = Category.parse(attrib['category'])
                children = [rec(spans[child]) for child in attrib['child'].split(' ')]
                if len(children) == 1:
                    return Tree.make_unary(cat, children[0], lang)
                else:
                    assert len(children) == 2
                    left, right = children
                    combinator = guess_combinator_by_triplet(
                                    binary_rules, cat, left.cat, right.cat)
                    combinator = combinator or UNKNOWN_COMBINATOR
                    return Tree.make_binary(cat, left, right, combinator, lang)
            else:
                cat = Category.parse(attrib['category'])
                word = try_get_surface(tokens[attrib['terminal']])
                return Tree.make_terminal(word, cat, lang)
github masashi-y / depccg / depccg / tools / reader.py View on Github external
def rec(node):
            attrib = node.attrib
            if node.tag == 'rule':
                cat = Category.parse(attrib['cat'])
                children = [rec(child) for child in node.getchildren()]
                if len(children) == 1:
                    return Tree.make_unary(cat, children[0], lang)
                else:
                    assert len(children) == 2
                    left, right = children
                    combinator = guess_combinator_by_triplet(
                                    binary_rules, cat, left.cat, right.cat)
                    combinator = combinator or UNKNOWN_COMBINATOR
                    return Tree.make_binary(cat, left, right, combinator, lang)
            else:
                assert node.tag == 'lf'
                cat = Category.parse(attrib['cat'])
                word = attrib['word']
                token = Token(word=attrib['word'],
                              pos=attrib['pos'],
                              entity=attrib['entity'],
                              lemma=attrib['lemma'],
                              chunk=attrib['chunk'])