File size: 1,440 Bytes
aaed6d7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 |
from oie_readers.oieReader import OieReader
from oie_readers.extraction import Extraction
class PropSReader(OieReader):
def __init__(self):
self.name = 'PropS'
def read(self, fn):
d = {}
with open(fn) as fin:
for line in fin:
if not line.strip():
continue
data = line.strip().split('\t')
confidence, text, rel = data[:3]
curExtraction = Extraction(pred = rel, sent = text, confidence = float(confidence), head_pred_index=-1)
for arg in data[4::2]:
curExtraction.addArg(arg)
d[text] = d.get(text, []) + [curExtraction]
self.oie = d
# self.normalizeConfidence()
def normalizeConfidence(self):
''' Normalize confidence to resemble probabilities '''
EPSILON = 1e-3
self.confidences = [extraction.confidence for sent in self.oie for extraction in self.oie[sent]]
maxConfidence = max(self.confidences)
minConfidence = min(self.confidences)
denom = maxConfidence - minConfidence + (2*EPSILON)
for sent, extractions in self.oie.items():
for extraction in extractions:
extraction.confidence = ( (extraction.confidence - minConfidence) + EPSILON) / denom
|