def main():
try:
sentences = sys.stdin.readlines()
model_file = sys.argv[1]
except:
raise ValueError('''Usage: cat <file of sentences> | python parse.py <model_file>
or, python parse.py <model_file>, type sentences and hit Ctrl+d''')
if not os.path.isfile(model_file):
raise ValueError('cant find the model file')
# scrub list / remove line breaks
sentences = [sent.rstrip() for sent in sentences]
# generate dependency graph object from sentences
depgraphs = [DependencyGraph.from_sentence(sent) for sent in sentences]
# load model and parse
tp = TransitionParser.load(model_file)
parsed = tp.parse(depgraphs)
# print to stdout.
# can cat this to a conll file for viewing with MaltEval
for p in parsed:
print(p.to_conll(10).encode('utf-8'))
return
def main():
file_to_parse = sys.stdin
sentences_list = [s for s in file_to_parse]
file_to_parse.close()
lang_model = sys.argv[1]
tp = TransitionParser.load(lang_model)
sentences = [DependencyGraph.from_sentence(s) for s in sentences_list]
parsed = tp.parse(sentences)
for p in parsed:
print p.to_conll(10).encode('utf-8')
def parse(argv):
if len(argv) != 2:
sys.exit( "python parse.py language.model")
# data = dataset.get_english_train_corpus().parsed_sents()
# random.seed(1234)
# subdata = random.sample(data, 200)
language_model = argv[1]
try:
sentences = sys.stdin.readlines()
for i,sentence in enumerate(sentences):
dg = DependencyGraph.from_sentence(sentence)
tp = TransitionParser.load(language_model)
parsed = tp.parse([dg])
print parsed[0].to_conll(10).encode('utf-8')
# tp = TransitionParser(Transition, FeatureExtractor)
# tp.train(subdata)
# tp.save('english.model')
# testdata = dataset.get_swedish_test_corpus().parsed_sents()
# tp = TransitionParser.load('english.model')
# parsed = tp.parse(testdata)
#open new file for write on first sentence
if i == 0:
with open('test.conll', 'w') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
f.write('\n')
#append for rest sentences
else:
with open('test.conll', 'a') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
f.write('\n')
# ev = DependencyEvaluator(testdata, parsed)
# print "UAS: {} \nLAS: {}".format(*ev.eval())
except NotImplementedError:
print """
from providedcode import dataset
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.dependencygraph import DependencyGraph
if __name__ == '__main__':
testdata = []
for line in sys.stdin:
sentence = DependencyGraph.from_sentence(line)
testdata.append(sentence)
model = sys.argv[1]
tp = TransitionParser.load(model)
parsed = tp.parse(testdata)
for p in parsed:
print(p.to_conll(10).encode('utf-8'))
# testdata = dataset.get_swedish_test_corpus().parsed_sents()
# tp = TransitionParser.load('badfeatures.model')
#parsed = tp.parse(testdata)
#with open('test.conll', 'w') as f:
# for p in parsed:
# f.write(p.to_conll(10).encode('utf-8'))
# f.write('\n')
#ev = DependencyEvaluator(testdata, parsed)
#print "LAS: {} \nUAS: {}".format(*ev.eval())
# parsing arbitrary sentences (english):
sentence = DependencyGraph.from_sentence('Hi, this is a test')
print sentence
print "model loading"
tp = TransitionParser.load('badfeatures.model')
print "model loaded"
print "sentence parsing"
parsed = tp.parse([sentence])
print "sentence parsed"
print parsed[0].to_conll(10).encode('utf-8')
except NotImplementedError:
print """
This file is currently broken! We removed the implementation of Transition
(in transition.py), which tells the transitionparser how to go from one
Configuration to another Configuration. This is an essential part of the
arc-eager dependency parsing algorithm, so you should probably fix that :)
# tp = TransitionParser.load('badfeatures.model')
# testdata = dataset.get_english_test_corpus().parsed_sents()
# tp = TransitionParser.load('english.model')
parsed = tp.parse(testdata)
with open('test.conll', 'w') as f:
for p in parsed:
f.write(p.to_conll(10).encode('utf-8'))
f.write('\n')
ev = DependencyEvaluator(testdata, parsed)
print "LAS: {} \nUAS: {}".format(*ev.eval())
# parsing arbitrary sentences (english):
sentence = DependencyGraph.from_sentence('Hi, this is a test')
tp = TransitionParser.load('english.model')
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
except NotImplementedError:
print """
This file is currently broken! We removed the implementation of Transition
(in transition.py), which tells the transitionparser how to go from one
Configuration to another Configuration. This is an essential part of the
arc-eager dependency parsing algorithm, so you should probably fix that :)
The algorithm is described in great detail here:
http://aclweb.org/anthology//C/C12/C12-1059.pdf
We also haven't actually implemented most of the features for for the
def handle_input(input_file, model_file):
tp = TransitionParser.load(model_file)
for line in input_file:
sentence = DependencyGraph.from_sentence(line)
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.dependencygraph import DependencyGraph
if __name__ == '__main__':
sentences = sys.stdin.readlines()
tp = TransitionParser.load(sys.argv[1])
for sentence in sentences:
dg = DependencyGraph.from_sentence(sentence)
parsed = tp.parse([dg])
print parsed[0].to_conll(10).encode('utf-8')
#print '\n'
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.dependencygraph import DependencyGraph
if __name__ == '__main__':
# the raw sentences read from englishfile
lines = sys.stdin
# if no sentences read or not enough parameters retrieved, exit the program.
if not lines or not sys.argv.__len__() == 2:
exit()
# put the raw sentences in to dependency graphs and form a list of these graphs.
sentences = [DependencyGraph.from_sentence(line) for line in lines]
model_name = sys.argv[1]
# load the trained model
tp = TransitionParser.load(model_name)
# parse the sentences with the model
parsed = tp.parse(sentences)
# write the parsed sentences into the output file conll supported format.
for parsed_line in parsed:
print parsed_line.to_conll(10).encode('utf-8')
#sentence = DependencyGraph.from_sentence('Hi, this is a test')
#tp = TransitionParser.load('english.model')
#parsed = tp.parse([sentence])
#print parsed[0].to_conll(10).encode('utf-8')
import random
from providedcode.dependencygraph import DependencyGraph
from providedcode import dataset
from providedcode.transitionparser import TransitionParser
from providedcode.evaluate import DependencyEvaluator
from featureextractor import FeatureExtractor
from transition import Transition
import sys
if __name__ == "__main__":
try:
# parsing arbitrary sentences (english):
fromInput = "".join(sys.stdin.readlines())
# print fromInput
sentence = DependencyGraph.from_sentence(fromInput)
tp = TransitionParser.load("english.model")
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode("utf-8")
except NotImplementedError:
print """
This file is currently broken! We removed the implementation of Transition
(in transition.py), which tells the transitionparser how to go from one
Configuration to another Configuration. This is an essential part of the
arc-eager dependency parsing algorithm, so you should probably fix that :)
The algorithm is described in great detail here:
http://aclweb.org/anthology//C/C12/C12-1059.pdf
We also haven't actually implemented most of the features for for the
support vector machine (in featureextractor.py), so as you might expect the
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.evaluate import DependencyEvaluator
from featureextractor import FeatureExtractor
from providedcode.dependencygraph import DependencyGraph
from transition import Transition
if __name__ == "__main__":
sentences = []
try:
while 1:
sentence = raw_input().strip()
sentences.append(DependencyGraph.from_sentence(sentence))
except EOFError:
pass
tp = TransitionParser.load(sys.argv[1])
parsed = tp.parse(sentences)
for p in parsed:
print p.to_conll(10).encode("utf-8")
import sys
if __name__ == '__main__':
try:
model = sys.argv[1]
tp = TransitionParser.load(model)
for line in sys.stdin:
# temp = line.strip()
# temp = str(temp)
# parsing arbitrary sentences (english):
# print "[" + temp + "]"
temp = line
# temp = "Hi, this is a test."
sentence = DependencyGraph.from_sentence(temp)
for key, dct in sentence.nodes.items():
dct['ctag'] = nltk.tag.mapping.map_tag("en-ptb", "universal", dct['ctag'])
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
except NotImplementedError:
print """
This file is currently broken! We removed the implementation of Transition
(in transition.py), which tells the transitionparser how to go from one
Configuration to another Configuration. This is an essential part of the
arc-eager dependency parsing algorithm, so you should probably fix that :)
The algorithm is described in great detail here:
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.evaluate import DependencyEvaluator
from providedcode.dependencygraph import DependencyGraph
from nltk.tag import mapping
if len(sys.argv) != 2:
sys.stderr.write("No model provided.")
sys.exit(1)
tp = TransitionParser.load(sys.argv[1])
for sentence in sys.stdin:
s = DependencyGraph.from_sentence(sentence) #class DependencyGraph, function from_sentence
for node in s.nodes:
tag = s.nodes[node]['tag']
ctag = mapping.map_tag('wsj','universal',tag)
s.nodes[node]['ctag'] = ctag
x = tp.parse([s])
print x[0].to_conll(10).encode('utf-8')
# model: sys.argv(1) - english.model
def handle_input(input_file, model_file):
tp = TransitionParser.load(model_file)
for line in input_file:
sentence = DependencyGraph.from_sentence(line)
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
import sys
from providedcode.transitionparser import TransitionParser
from providedcode.dependencygraph import DependencyGraph
if __name__ == '__main__':
model = sys.argv[1]
data = sys.stdin.readlines()
for item in data:
sentence = DependencyGraph.from_sentence(item)
tp = TransitionParser.load(model)
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
sys.stdout.flush()
__author__ = 'johnfulgoni'
import sys
from providedcode.dependencygraph import DependencyGraph
from providedcode.transitionparser import TransitionParser
# DON'T PRINT ANYTHING! OR ELSE IT MESSES THINGS UP
if __name__ == '__main__':
argc = len(sys.argv)
if argc == 2:
#print sys.argv[1] # just to see
sentence_list = []
for sent in sys.stdin: # get the sentences from the englishfile
sentence = DependencyGraph.from_sentence(sent)
sentence_list.append(sentence)
my_model = sys.argv[1] # should be 'english.model'
tp = TransitionParser.load(my_model)
parsed = tp.parse(sentence_list)
# following the example in test.py
# but we're not writing it to a file
for p in parsed:
print p.to_conll(10).encode('utf-8')
print '\n'
else:
print "Need two arguments"
exit(1)
import providedcode
from providedcode.transitionparser import TransitionParser
from providedcode.dependencygraph import DependencyGraph
from providedcode.evaluate import DependencyEvaluator
import sys
tp = TransitionParser.load('english.model')
for line in sys.stdin:
sentence = DependencyGraph.from_sentence(line)
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8')
import sys
import fileinput
from providedcode.transitionparser import TransitionParser
from providedcode import dataset
from providedcode.dependencygraph import DependencyGraph
englishfile = sys.stdin.read()
lines = englishfile.split('\n')
model = sys.argv[1]
tp = TransitionParser.load(model)
for line in lines:
sentence = DependencyGraph.from_sentence(line.strip())
parsed = tp.parse([sentence])
print parsed[0].to_conll(10).encode('utf-8'), ('\n')