class CNLP:
CNLPServerURL = 'http://localhost:9000'
def __init__(self):
self.parser = CoreNLPParser(url=self.CNLPServerURL)
self.dep_parser = CoreNLPDependencyParser(url=self.CNLPServerURL)
self.ner_tagger = CoreNLPParser(url=self.CNLPServerURL, tagtype='ner')
self.pos_tagger = CoreNLPParser(url=self.CNLPServerURL, tagtype='pos')
def getParse(self, sentence):
if (type(sentence) == list):
return self.parser.parse(sentence)
else:
return self.parser.raw_parse(sentence)
def getDepParse(self, sentence):
if (type(sentence) == list):
return self.dep_parser.parse(sentence)
else:
return self.dep_parser.raw_parse(sentence)
def getNERTags(self, sentence):
if (type(sentence) != list):
sentence = sentence.split()
return self.ner_tagger.tag(sentence)
def getPOSTags(self, sentence):
if (type(sentence) == list):
return self.pos_tagger.parse(sentence)
else:
return self.pos_tagger.raw_parse(sentence)
def convert_eng_to_isl(input_string):
if len(list(input_string.split(' '))) is 1:
return list(input_string.split(' '))
# Initializing stanford parser
parser = CoreNLPParser()
# Generates all possible parse trees sort by probability for the sentence
possible_parse_tree_list = [tree for tree in parser.parse(input_string.split())]
# Get most probable parse tree
parse_tree = possible_parse_tree_list[0]
# print(parse_tree)
# output = '(ROOT
# (S
# (PP (IN As) (NP (DT an) (NN accountant)))
# (NP (PRP I))
# (VP (VBP want) (S (VP (TO to) (VP (VB make) (NP (DT a) (NN payment))))))
# )
# )'
# Convert into tree data structure
parent_tree = ParentedTree.convert(parse_tree)
print("\n\nParse Tree:\n")
print(parent_tree)
modified_parse_tree = modify_tree_structure(parent_tree)
print("\n\nModified Parse Tree:\n")
print(modified_parse_tree)
isl_sentence = modified_parse_tree.leaves()
return isl_sentence
def convert_sentence(input_string: str):
java_path = '/usr/bin/java'
os.environ['CLASSPATH'] = java_path
if input_string.split() == 1:
return None
if len(input_string.split()) == 1:
path = create_video(input_string)
return path
parser = CoreNLPParser(url='http://localhost:9000')
englishtree = [tree for tree in parser.parse(input_string.split())]
parsetree = englishtree[0]
dict = {}
# parenttree = ParentedTree(node=parsetree, children=[])
parenttree = ParentedTree.fromstring(str(parsetree))
# print("Input Sentence: ", input_string)
# print("Input Sentence Tree\n")
# print(parenttree)
print("\n\n")
for sub in parenttree.subtrees():
dict[sub.treeposition()] = 0
#----------------------------#
islTree = Tree('ROOT', [])
i = 0
for sub in parenttree.subtrees():
if (sub.label() == "NP" and dict[sub.treeposition()] == 0
and dict[sub.parent().treeposition()] == 0):
dict[sub.treeposition()] = 1
islTree.insert(i, sub)
i = i + 1
if (sub.label() == "VP" or sub.label() == "PRP"):
for sub2 in sub.subtrees():
if ((sub2.label() == "NP" or sub2.label() == 'PRP')
and dict[sub2.treeposition()] == 0
and dict[sub2.parent().treeposition()] == 0):
dict[sub2.treeposition()] = 1
islTree.insert(i, sub2)
i = i + 1
for sub in parenttree.subtrees():
for sub2 in sub.subtrees():
if (len(sub2.leaves()) == 1 and dict[sub2.treeposition()] == 0
and dict[sub2.parent().treeposition()] == 0):
dict[sub2.treeposition()] = 1
islTree.insert(i, sub2)
i = i + 1
parsed_sent = islTree.leaves()
# words = parsed_sent
# print("ISL Tree\n")
# print(islTree)
# print("\n\n")
# nltk.download('stopwords')
# nltk.download('wordnet')
# print()
stop_words = set(stopwords.words("english"))
lemmantizer = WordNetLemmatizer()
# ps = PorterStemmer()
lemmantized_words = []
for w in parsed_sent:
# w = ps.stem(w)
lemmantized_words.append(lemmantizer.lemmatize(w))
islSentence = ""
for w in lemmantized_words:
if w not in stop_words:
islSentence += w
islSentence += " "
# islSentence += w
# islSentence += " "
# print("ISL Sentence\n")
# print(islSentence)
# print("\n\n")
path = create_video(islSentence)
return path
import stanza
# Inizializing stanza
# stanza.download('em')
message = 'I live in Mexico'
nlp = stanza.Pipeline('en', processors='tokenize,pos')
doc = nlp(message)
# set java path
import os
java_path = r'C:\Program Files\Java\jdk1.8.0_161\bin\java.exe'
os.environ['JAVAHOME'] = java_path
from nltk.parse.stanford import StanfordParser
scp = StanfordParser(
path_to_jar=
'C:/Users/carvi/Documents/Proyectos/NLP/stanford-parser-4.0.0/stanford-parser.jar',
path_to_models_jar=
'C:/Users/carvi/Documents/Proyectos/NLP/stanford-parser-4.0.0/stanford-parser-4.0.0-models.jar'
)
result = list(scp.raw_parse(message))
print(result[0])
from nltk.parse.corenlp import CoreNLPParser
prueba = CoreNLPParser.parse(message)
print(prueba)
