peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/nltk
/sem
/lfg.py
# Natural Language Toolkit: Lexical Functional Grammar | |
# | |
# Author: Dan Garrette <[email protected]> | |
# | |
# Copyright (C) 2001-2023 NLTK Project | |
# URL: <https://www.nltk.org/> | |
# For license information, see LICENSE.TXT | |
from itertools import chain | |
from nltk.internals import Counter | |
class FStructure(dict): | |
def safeappend(self, key, item): | |
""" | |
Append 'item' to the list at 'key'. If no list exists for 'key', then | |
construct one. | |
""" | |
if key not in self: | |
self[key] = [] | |
self[key].append(item) | |
def __setitem__(self, key, value): | |
dict.__setitem__(self, key.lower(), value) | |
def __getitem__(self, key): | |
return dict.__getitem__(self, key.lower()) | |
def __contains__(self, key): | |
return dict.__contains__(self, key.lower()) | |
def to_glueformula_list(self, glue_dict): | |
depgraph = self.to_depgraph() | |
return glue_dict.to_glueformula_list(depgraph) | |
def to_depgraph(self, rel=None): | |
from nltk.parse.dependencygraph import DependencyGraph | |
depgraph = DependencyGraph() | |
nodes = depgraph.nodes | |
self._to_depgraph(nodes, 0, "ROOT") | |
# Add all the dependencies for all the nodes | |
for address, node in nodes.items(): | |
for n2 in (n for n in nodes.values() if n["rel"] != "TOP"): | |
if n2["head"] == address: | |
relation = n2["rel"] | |
node["deps"].setdefault(relation, []) | |
node["deps"][relation].append(n2["address"]) | |
depgraph.root = nodes[1] | |
return depgraph | |
def _to_depgraph(self, nodes, head, rel): | |
index = len(nodes) | |
nodes[index].update( | |
{ | |
"address": index, | |
"word": self.pred[0], | |
"tag": self.pred[1], | |
"head": head, | |
"rel": rel, | |
} | |
) | |
for feature in sorted(self): | |
for item in sorted(self[feature]): | |
if isinstance(item, FStructure): | |
item._to_depgraph(nodes, index, feature) | |
elif isinstance(item, tuple): | |
new_index = len(nodes) | |
nodes[new_index].update( | |
{ | |
"address": new_index, | |
"word": item[0], | |
"tag": item[1], | |
"head": index, | |
"rel": feature, | |
} | |
) | |
elif isinstance(item, list): | |
for n in item: | |
n._to_depgraph(nodes, index, feature) | |
else: | |
raise Exception( | |
"feature %s is not an FStruct, a list, or a tuple" % feature | |
) | |
def read_depgraph(depgraph): | |
return FStructure._read_depgraph(depgraph.root, depgraph) | |
def _read_depgraph(node, depgraph, label_counter=None, parent=None): | |
if not label_counter: | |
label_counter = Counter() | |
if node["rel"].lower() in ["spec", "punct"]: | |
# the value of a 'spec' entry is a word, not an FStructure | |
return (node["word"], node["tag"]) | |
else: | |
fstruct = FStructure() | |
fstruct.pred = None | |
fstruct.label = FStructure._make_label(label_counter.get()) | |
fstruct.parent = parent | |
word, tag = node["word"], node["tag"] | |
if tag[:2] == "VB": | |
if tag[2:3] == "D": | |
fstruct.safeappend("tense", ("PAST", "tense")) | |
fstruct.pred = (word, tag[:2]) | |
if not fstruct.pred: | |
fstruct.pred = (word, tag) | |
children = [ | |
depgraph.nodes[idx] | |
for idx in chain.from_iterable(node["deps"].values()) | |
] | |
for child in children: | |
fstruct.safeappend( | |
child["rel"], | |
FStructure._read_depgraph(child, depgraph, label_counter, fstruct), | |
) | |
return fstruct | |
def _make_label(value): | |
""" | |
Pick an alphabetic character as identifier for an entity in the model. | |
:param value: where to index into the list of characters | |
:type value: int | |
""" | |
letter = [ | |
"f", | |
"g", | |
"h", | |
"i", | |
"j", | |
"k", | |
"l", | |
"m", | |
"n", | |
"o", | |
"p", | |
"q", | |
"r", | |
"s", | |
"t", | |
"u", | |
"v", | |
"w", | |
"x", | |
"y", | |
"z", | |
"a", | |
"b", | |
"c", | |
"d", | |
"e", | |
][value - 1] | |
num = int(value) // 26 | |
if num > 0: | |
return letter + str(num) | |
else: | |
return letter | |
def __repr__(self): | |
return self.__str__().replace("\n", "") | |
def __str__(self): | |
return self.pretty_format() | |
def pretty_format(self, indent=3): | |
try: | |
accum = "%s:[" % self.label | |
except NameError: | |
accum = "[" | |
try: | |
accum += "pred '%s'" % (self.pred[0]) | |
except NameError: | |
pass | |
for feature in sorted(self): | |
for item in self[feature]: | |
if isinstance(item, FStructure): | |
next_indent = indent + len(feature) + 3 + len(self.label) | |
accum += "\n{}{} {}".format( | |
" " * (indent), | |
feature, | |
item.pretty_format(next_indent), | |
) | |
elif isinstance(item, tuple): | |
accum += "\n{}{} '{}'".format(" " * (indent), feature, item[0]) | |
elif isinstance(item, list): | |
accum += "\n{}{} {{{}}}".format( | |
" " * (indent), | |
feature, | |
("\n%s" % (" " * (indent + len(feature) + 2))).join(item), | |
) | |
else: # ERROR | |
raise Exception( | |
"feature %s is not an FStruct, a list, or a tuple" % feature | |
) | |
return accum + "]" | |
def demo_read_depgraph(): | |
from nltk.parse.dependencygraph import DependencyGraph | |
dg1 = DependencyGraph( | |
"""\ | |
Esso NNP 2 SUB | |
said VBD 0 ROOT | |
the DT 5 NMOD | |
Whiting NNP 5 NMOD | |
field NN 6 SUB | |
started VBD 2 VMOD | |
production NN 6 OBJ | |
Tuesday NNP 6 VMOD | |
""" | |
) | |
dg2 = DependencyGraph( | |
"""\ | |
John NNP 2 SUB | |
sees VBP 0 ROOT | |
Mary NNP 2 OBJ | |
""" | |
) | |
dg3 = DependencyGraph( | |
"""\ | |
a DT 2 SPEC | |
man NN 3 SUBJ | |
walks VB 0 ROOT | |
""" | |
) | |
dg4 = DependencyGraph( | |
"""\ | |
every DT 2 SPEC | |
girl NN 3 SUBJ | |
chases VB 0 ROOT | |
a DT 5 SPEC | |
dog NN 3 OBJ | |
""" | |
) | |
depgraphs = [dg1, dg2, dg3, dg4] | |
for dg in depgraphs: | |
print(FStructure.read_depgraph(dg)) | |
if __name__ == "__main__": | |
demo_read_depgraph() | |