def __init__(self, path="SentiWordNet*.txt", language="en"):
"""A sentiment lexicon with scores from SentiWordNet.
The value for each word is a tuple with values for
polarity (-1.0-1.0), subjectivity (0.0-1.0) and intensity (0.5-2.0).
"""
Sentiment.__init__(self, path=path, language=language)
def load(self, path=None):
_Sentiment.load(self, path)
# Map "verschrikkelijk" to adverbial "verschrikkelijke" (+1%)
if not path:
for w, pos in list(dict.items(self)):
if "JJ" in pos:
p, s, i = pos["JJ"]
self.annotate(attributive(w), "JJ", p, s, i)
def load(self, path=None):
_Sentiment.load(self, path)
# Map "terrible" to adverb "terribly" (+1% accuracy)
if not path:
for w, pos in list(dict.items(self)):
if "JJ" in pos:
if w.endswith("y"):
w = w[:-1] + "i"
if w.endswith("le"):
w = w[:-2]
p, s, i = pos["JJ"]
self.annotate(w + "ly", "RB", p, s, i)
def load(self, path=None):
_Sentiment.load(self, path)
# Map "précaire" to "precaire" (without diacritics, +1% accuracy).
if not path:
for w, pos in list(dict.items(self)):
w0 = w
if not w.endswith(("à", "è", "é", "ê", "ï")):
w = w.replace("à", "a")
w = w.replace("é", "e")
w = w.replace("è", "e")
w = w.replace("ê", "e")
w = w.replace("ï", "i")
if w != w0:
for pos, (p, s, i) in list(pos.items()):
self.annotate(w, pos, p, s, i)
def get(self, k, *args, **kwargs):
return Sentiment.get(self, normalize(k), *args, **kwargs)
def __getitem__(self, k):
return Sentiment.__getitem__(self, normalize(k))