def tree2():
tree = ConstituentTree("1")
for i, t in enumerate(["a", "b", "d", "c"]):
tree.add_leaf(str(i), "P" + t, t)
tree.set_label('r0', 'C')
tree.set_label('r1', 'A')
tree.set_label('r2', 'B')
tree.add_to_root('r0')
tree.add_child('r0', 'r1')
tree.add_child('r0', 'r2')
tree.add_child('r1', '0')
tree.add_child('r1', '3')
tree.add_child('r2', '1')
tree.add_child('r2', '2')
print(tree, tree.word_yield())
return tree
def constituent_tree_1_pos_stripped():
tree = ConstituentTree("s1")
tree.add_leaf("f1", "--", "hat")
tree.add_leaf("f2", "--", "schnell")
tree.add_leaf("f3", "--", "gearbeitet")
tree.add_punct("f4", "--", ".")
tree.set_label("V", "V")
tree.add_child("V", "f1")
tree.add_child("V", "f3")
tree.set_label("ADV", "ADV")
tree.add_child("ADV", "f2")
tree.set_label("VP", "VP")
tree.add_child("VP", "V")
tree.add_child("VP", "ADV")
tree.add_to_root("VP")
return tree
def constituent_tree_2():
tree = ConstituentTree("s2")
tree.add_leaf("l1", "N", "John")
tree.add_leaf("l2", "V", "hit")
tree.add_leaf("l3", "D", "the")
tree.add_leaf("l4", "N", "Ball")
tree.add_punct("l5", "PUNC", ".")
tree.set_label("NP", "NP")
tree.add_child("NP", "l3")
tree.add_child("NP", "l4")
tree.set_label("VP", "VP")
tree.add_child("VP", "l2")
tree.add_child("VP", "NP")
tree.set_label("S", "S")
tree.add_child("S", "l1")
tree.add_child("S", "VP")
tree.add_to_root("S")
return tree
def setUp(self):
tree = ConstituentTree("s1")
tree.add_leaf("f1",
"VAFIN",
"hat",
morph=[("number", "Sg"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
tree.add_leaf("f3", "VVPP", "gearbeitet")
tree.add_punct("f4", "PUNC", ".")
tree.add_child("VP2", "f1")
tree.add_child("VP2", "f3")
tree.add_child("ADVP", "f2")
tree.add_child("VP1", "VP2")
tree.add_child("VP1", "ADVP")
tree.set_label("VP2", "VP")
tree.set_label("VP1", "VP")
tree.set_label("ADVP", "ADVP")
self.tree = tree
tree2 = ConstituentTree("s2")
tree2.add_leaf("f1",
"VAFIN",
"haben",
morph=[("number", "Pl"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
tree2.add_leaf("f3", "VVPP", "gekocht")
tree2.add_punct("f4", "PUNC", ".")
tree2.add_child("VP2", "f1")
tree2.add_child("VP2", "f3")
tree2.add_child("ADVP", "f2")
tree2.add_child("VP1", "VP2")
tree2.add_child("VP1", "ADVP")
tree2.set_label("VP2", "VP")
tree2.set_label("VP1", "VP")
tree2.set_label("ADVP", "ADVP")
tree2.add_to_root("VP1")
self.tree2 = tree2
self.tree3 = ConstituentTree("s3")
self.tree3.add_leaf("f1",
"ADJA",
"Allgemeiner",
edge="NK",
morph=[("number", "Sg")])
self.tree3.add_leaf("f2",
"ADJA",
"Deutscher",
edge="NK",
morph=[("degree", "Pos"), ("number", "Sg")])
self.tree3.add_leaf("f3",
"NN",
"Fahrrad",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
self.tree3.add_leaf("f4",
"NN",
"Club",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
for i in range(1, 5):
self.tree3.add_child("NP", "f" + str(i))
self.tree3.set_label("NP", "NP")
self.tree3.add_to_root("NP")
class ConstituentTreeTest(unittest.TestCase):
def test_something(self):
tree = self.tree
print("rooted", tree.root)
tree.add_to_root("VP1")
print("rooted", tree.root)
print(tree)
print("sent label", tree.sent_label())
print("leaves", tree.leaves())
print("is leaf (leaves)",
[(x, tree.is_leaf(x)) for (x, _, _) in tree.leaves()])
print("is leaf (internal)", [(x, tree.is_leaf(x)) for x in tree.ids()])
print("leaf index",
[(x, tree.leaf_index(x)) for x in ["f1", "f2", "f3"]])
print("pos yield", tree.pos_yield())
print("word yield", tree.word_yield())
# reentrant
# parent
print("ids", tree.ids())
# reorder
print("n nodes", tree.n_nodes())
print("n gaps", tree.n_gaps())
print("fringe VP", tree.fringe("VP"))
print("fringe V", tree.fringe("V"))
print("empty fringe", tree.empty_fringe())
print("complete?", tree.complete())
print("max n spans", tree.max_n_spans())
print("unlabelled structure", tree.unlabelled_structure())
print("labelled spans", tree.labelled_spans())
def test_induction(self):
naming = 'child'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
# return fanout_k_left_to_right(tree, 1)
tree = self.tree
tree.add_to_root("VP1")
feature_log1 = defaultdict(lambda: 0)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
feature_logging=feature_log1,
naming=naming)
for key in feature_log1:
print(key, feature_log1[key])
print(grammar)
feats = defaultdict(lambda: 0)
grammar_ = fringe_extract_lcfrs(tree,
rec_part(tree),
isolate_pos=True,
feature_logging=feats,
naming=naming)
print(grammar_)
for key in feats:
print(key, feats[key])
print("Adding 2nd grammar to first")
grammar.add_gram(grammar_, feature_logging=(feature_log1, feats))
for idx in range(0, len(grammar.rules())):
print(idx, grammar.rule_index(idx))
print("Adding 3rd grammar to first")
feats3 = defaultdict(lambda: 0)
grammar3 = fringe_extract_lcfrs(self.tree2,
rec_part(self.tree2),
isolate_pos=True,
feature_logging=feats3,
naming=naming)
grammar.add_gram(grammar3, feature_logging=(feature_log1, feats3))
print()
for idx in range(0, len(grammar.rules())):
print(idx, grammar.rule_index(idx))
print()
print("New feature log")
print()
for key in feature_log1:
print(key, feature_log1[key])
grammar.make_proper()
build_nont_splits_dict(grammar,
feature_log1,
nonterminals=Enumerator())
print(grammar.rule_index(0))
print(grammar.rule_index(2))
def test_markovized_induction(self):
naming = 'strict-markov-v-2-h-0'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
# return fanout_k_left_to_right(tree, 1)
tree = self.tree
tree.add_to_root("VP1")
print(tree)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
naming=naming,
isolate_pos=True)
print(grammar)
def test_induction_2(self):
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
features = defaultdict(lambda: 0)
grammar = fringe_extract_lcfrs(self.tree3,
rec_part(self.tree3),
naming="child",
feature_logging=features,
isolate_pos=True)
grammar.make_proper()
if False:
for idx in range(0, len(grammar.rules())):
print(grammar.rule_index(idx))
for key in features:
if key[0] == idx:
print(key, features[key])
print()
for key in features:
if type(key[0]) == int:
continue
print(key, features[key])
nont_splits, root_weights, rule_weights, _ = build_nont_splits_dict(
grammar,
features,
nonterminals=Enumerator(),
feat_function=pos_cat_feats,
debug=True)
print(nont_splits)
print(root_weights)
print(rule_weights)
def setUp(self):
tree = ConstituentTree("s1")
tree.add_leaf("f1",
"VAFIN",
"hat",
morph=[("number", "Sg"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
tree.add_leaf("f3", "VVPP", "gearbeitet")
tree.add_punct("f4", "PUNC", ".")
tree.add_child("VP2", "f1")
tree.add_child("VP2", "f3")
tree.add_child("ADVP", "f2")
tree.add_child("VP1", "VP2")
tree.add_child("VP1", "ADVP")
tree.set_label("VP2", "VP")
tree.set_label("VP1", "VP")
tree.set_label("ADVP", "ADVP")
self.tree = tree
tree2 = ConstituentTree("s2")
tree2.add_leaf("f1",
"VAFIN",
"haben",
morph=[("number", "Pl"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
tree2.add_leaf("f3", "VVPP", "gekocht")
tree2.add_punct("f4", "PUNC", ".")
tree2.add_child("VP2", "f1")
tree2.add_child("VP2", "f3")
tree2.add_child("ADVP", "f2")
tree2.add_child("VP1", "VP2")
tree2.add_child("VP1", "ADVP")
tree2.set_label("VP2", "VP")
tree2.set_label("VP1", "VP")
tree2.set_label("ADVP", "ADVP")
tree2.add_to_root("VP1")
self.tree2 = tree2
self.tree3 = ConstituentTree("s3")
self.tree3.add_leaf("f1",
"ADJA",
"Allgemeiner",
edge="NK",
morph=[("number", "Sg")])
self.tree3.add_leaf("f2",
"ADJA",
"Deutscher",
edge="NK",
morph=[("degree", "Pos"), ("number", "Sg")])
self.tree3.add_leaf("f3",
"NN",
"Fahrrad",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
self.tree3.add_leaf("f4",
"NN",
"Club",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
for i in range(1, 5):
self.tree3.add_child("NP", "f" + str(i))
self.tree3.set_label("NP", "NP")
self.tree3.add_to_root("NP")
class ConstituentTreeTest(unittest.TestCase):
def test_basic_tree_methods(self):
tree = self.tree
print("rooted", tree.root)
tree.add_to_root("VP1")
print("rooted", tree.root)
print(tree)
print("sent label", tree.sent_label())
print("leaves", tree.leaves())
print("is leaf (leaves)",
[(x, tree.is_leaf(x)) for (x, _, _) in tree.leaves()])
print("is leaf (internal)", [(x, tree.is_leaf(x)) for x in tree.ids()])
print("leaf index",
[(x, tree.leaf_index(x)) for x in ["f1", "f2", "f3"]])
print("pos yield", tree.pos_yield())
print("word yield", tree.word_yield())
# reentrant
# parent
print("ids", tree.ids())
# reorder
print("n nodes", tree.n_nodes())
print("n gaps", tree.n_gaps())
print("fringe VP", tree.fringe("VP"))
print("fringe V", tree.fringe("V"))
print("empty fringe", tree.empty_fringe())
print("complete?", tree.complete())
print("max n spans", tree.max_n_spans())
print("unlabelled structure", tree.unlabelled_structure())
print("labelled spans", tree.labelled_spans())
def test_induction(self):
naming = 'child'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
# return fanout_k_left_to_right(tree, 1)
tree = self.tree
tree.add_to_root("VP1")
feature_log1 = defaultdict(lambda: 0)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
feature_logging=feature_log1,
naming=naming)
for key in feature_log1:
print(key, feature_log1[key])
print(grammar)
feats = defaultdict(lambda: 0)
grammar_ = fringe_extract_lcfrs(tree,
rec_part(tree),
isolate_pos=True,
feature_logging=feats,
naming=naming)
print(grammar_)
for key in feats:
print(key, feats[key])
print("Adding 2nd grammar to first")
grammar.add_gram(grammar_, feature_logging=(feature_log1, feats))
for idx in range(0, len(grammar.rules())):
print(idx, grammar.rule_index(idx))
print("Adding 3rd grammar to first")
feats3 = defaultdict(lambda: 0)
grammar3 = fringe_extract_lcfrs(self.tree2,
rec_part(self.tree2),
isolate_pos=True,
feature_logging=feats3,
naming=naming)
grammar.add_gram(grammar3, feature_logging=(feature_log1, feats3))
print()
for idx in range(0, len(grammar.rules())):
print(idx, grammar.rule_index(idx))
print()
print("New feature log")
print()
for key in feature_log1:
print(key, feature_log1[key])
grammar.make_proper()
build_nont_splits_dict(grammar,
feature_log1,
nonterminals=Enumerator())
print(grammar.rule_index(0))
print(grammar.rule_index(2))
def test_markovized_induction(self):
naming = 'strict-markov-v-2-h-0'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
# return fanout_k_left_to_right(tree, 1)
tree = self.tree
tree.add_to_root("VP1")
print(tree)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
naming=naming,
isolate_pos=True)
print(grammar)
def test_induction_and_parsing_with_pos_recovery(self):
naming = 'child'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
tree = self.tree
tree.add_to_root("VP1")
print(tree)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
naming=naming,
isolate_pos=True,
term_labeling=FormTerminals())
print(grammar)
parser = LCFRS_parser(grammar)
parser.set_input([token.form() for token in tree.token_yield()])
parser.parse()
self.assertTrue(parser.recognized())
derivation = parser.best_derivation_tree()
e = DCP_evaluator(derivation)
dcp_term = e.getEvaluation()
print(str(dcp_term[0]))
t = ConstituentTree()
dcp_to_hybridtree(
t,
dcp_term, [
construct_constituent_token(token.form(), '--', True)
for token in tree.token_yield()
],
ignore_punctuation=False,
construct_token=construct_constituent_token)
print(t)
self.assertEqual(len(tree.token_yield()), len(t.token_yield()))
for tok1, tok2 in zip(tree.token_yield(), t.token_yield()):
self.assertEqual(tok1.form(), tok2.form())
self.assertEqual(tok1.pos(), tok2.pos())
def test_stanford_unking_scheme(self):
naming = 'child'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
tree = self.tree
tree.add_to_root("VP1")
print(tree)
terminal_labeling = StanfordUNKing([tree])
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
naming=naming,
isolate_pos=True,
term_labeling=terminal_labeling)
print(grammar)
parser = LCFRS_parser(grammar)
parser.set_input([token.form() for token in tree.token_yield()])
parser.parse()
self.assertTrue(parser.recognized())
derivation = parser.best_derivation_tree()
e = DCP_evaluator(derivation)
dcp_term = e.getEvaluation()
print(str(dcp_term[0]))
t = ConstituentTree()
dcp_to_hybridtree(
t,
dcp_term, [
construct_constituent_token(token.form(), '--', True)
for token in tree.token_yield()
],
ignore_punctuation=False,
construct_token=construct_constituent_token)
print(t)
self.assertEqual(len(tree.token_yield()), len(t.token_yield()))
for tok1, tok2 in zip(tree.token_yield(), t.token_yield()):
self.assertEqual(tok1.form(), tok2.form())
self.assertEqual(tok1.pos(), tok2.pos())
rules = terminal_labeling.create_smoothed_rules()
print(rules)
new_rules = {}
for rule in grammar.rules():
if rule.rhs() == []:
assert len(rule.dcp()) == 1
dcp = rule.dcp()[0]
assert len(dcp.rhs()) == 1
term = dcp.rhs()[0]
head = term.head()
pos = head.pos()
for tag, form in rules:
if tag == pos:
lhs = LCFRS_lhs(rule.lhs().nont())
lhs.add_arg([form])
new_rules[lhs, dcp] = rules[tag, form]
for lhs, dcp in new_rules:
print(str(lhs), str(dcp), new_rules[(lhs, dcp)])
tokens = [
construct_constituent_token('hat', '--', True),
construct_constituent_token('HAT', '--', True)
]
self.assertEqual(terminal_labeling.token_label(tokens[0]), 'hat')
self.assertEqual(terminal_labeling.token_label(tokens[1]), '_UNK')
terminal_labeling.test_mode = True
self.assertEqual(terminal_labeling.token_label(tokens[0]), 'hat')
self.assertEqual(terminal_labeling.token_label(tokens[1]), 'hat')
def test_induction_with_spans(self):
naming = 'child-spans'
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
# return fanout_k_left_to_right(tree, 1)
tree = self.tree
tree.add_to_root("VP1")
print(tree)
grammar = fringe_extract_lcfrs(tree,
rec_part(tree),
naming=naming,
isolate_pos=True)
print(grammar)
def test_induction_2(self):
def rec_part(tree):
return left_branching_partitioning(len(tree.id_yield()))
features = defaultdict(lambda: 0)
grammar = fringe_extract_lcfrs(self.tree3,
rec_part(self.tree3),
naming="child",
feature_logging=features,
isolate_pos=True)
grammar.make_proper()
if False:
for idx in range(0, len(grammar.rules())):
print(grammar.rule_index(idx))
for key in features:
if key[0] == idx:
print(key, features[key])
print()
for key in features:
if type(key[0]) == int:
continue
print(key, features[key])
nont_splits, root_weights, rule_weights, _ = build_nont_splits_dict(
grammar,
features,
nonterminals=Enumerator(),
feat_function=pos_cat_feats,
debug=True)
print(nont_splits)
print(root_weights)
print(rule_weights)
def setUp(self):
tree = ConstituentTree("s1")
tree.add_leaf("f1",
"VAFIN",
"hat",
morph=[("number", "Sg"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree.add_leaf("f2", "ADV", "schnell", morph=[("degree", "Pos")])
tree.add_leaf("f3", "VVPP", "gearbeitet")
tree.add_punct("f4", "PUNC", ".")
tree.add_child("VP2", "f1")
tree.add_child("VP2", "f3")
tree.add_child("ADVP", "f2")
tree.add_child("VP1", "VP2")
tree.add_child("VP1", "ADVP")
tree.set_label("VP2", "VP")
tree.set_label("VP1", "VP")
tree.set_label("ADVP", "ADVP")
self.tree = tree
tree2 = ConstituentTree("s2")
tree2.add_leaf("f1",
"VAFIN",
"haben",
morph=[("number", "Pl"), ("person", "3"),
("tense", "Past"), ("mood", "Ind")])
tree2.add_leaf("f2", "ADV", "gut", morph=[("degree", "Pos")])
tree2.add_leaf("f3", "VVPP", "gekocht")
tree2.add_punct("f4", "PUNC", ".")
tree2.add_child("VP2", "f1")
tree2.add_child("VP2", "f3")
tree2.add_child("ADVP", "f2")
tree2.add_child("VP1", "VP2")
tree2.add_child("VP1", "ADVP")
tree2.set_label("VP2", "VP")
tree2.set_label("VP1", "VP")
tree2.set_label("ADVP", "ADVP")
tree2.add_to_root("VP1")
self.tree2 = tree2
self.tree3 = ConstituentTree("s3")
self.tree3.add_leaf("f1",
"ADJA",
"Allgemeiner",
edge="NK",
morph=[("number", "Sg")])
self.tree3.add_leaf("f2",
"ADJA",
"Deutscher",
edge="NK",
morph=[("degree", "Pos"), ("number", "Sg")])
self.tree3.add_leaf("f3",
"NN",
"Fahrrad",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
self.tree3.add_leaf("f4",
"NN",
"Club",
edge="NK",
morph=[("number", "Sg"), ("gender", "Neut")])
for i in range(1, 5):
self.tree3.add_child("NP", "f" + str(i))
self.tree3.set_label("NP", "NP")
self.tree3.add_to_root("NP")