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document.py
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document.py
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import util
import directories
import timer
from collections import defaultdict
import numpy as np
import evaluation
from collections import Counter
class Document:
def __init__(self, did, mentions, gold, mention_to_gold):
self.did = did
self.mentions = mentions
self.gold = gold
self.mention_to_gold = {m: tuple(g) for m, g in mention_to_gold.iteritems()}
self.reset()
def reset(self):
self.clusters = []
self.mention_to_cluster = {}
self.rs = {}
self.ps = {}
self.ana_to_ant = {}
self.ant_to_anas = {}
for m in self.mentions:
c = (m,)
self.mention_to_cluster[m] = c
self.clusters.append(c)
self.rs[m] = 0
self.ps[m] = 0
self.ana_to_ant[m] = -1
self.ant_to_anas[m] = []
self.p_num = self.r_num = self.p_den = 0
self.r_den = sum(len(g) for g in self.gold)
def get_f1(self, beta=1):
return evaluation.f1(self.p_num, self.p_den, self.r_num, self.r_den, beta=beta)
def update_b3(self, c, hypothetical=False):
timer.start("update b3")
if len(c) == 1:
self.p_den -= 1
self.p_num -= self.ps[c[0]]
self.r_num -= self.rs[c[0]]
self.ps[c[0]] = 0
self.rs[c[0]] = 0
else:
intersect_counts = Counter()
for m in c:
if m in self.mention_to_gold:
intersect_counts[self.mention_to_gold[m]] += 1
for m in c:
if m in self.mention_to_gold:
self.p_num -= self.ps[m]
self.r_num -= self.rs[m]
g = self.mention_to_gold[m]
ic = intersect_counts[g]
self.p_num += ic / float(len(c))
self.r_num += ic / float(len(g))
if not hypothetical:
self.ps[m] = ic / float(len(c))
self.rs[m] = ic / float(len(g))
timer.stop("update b3")
def link(self, m1, m2, hypothetical=False, beta=1):
timer.start("link")
if m1 == -1:
return self.get_f1(beta=beta) if hypothetical else None
c1, c2 = self.mention_to_cluster[m1], self.mention_to_cluster[m2]
assert c1 != c2
new_c = c1 + c2
p_num, r_num, p_den, r_den = self.p_num, self.r_num, self.p_den, self.r_den
if len(c1) == 1:
self.p_den += 1
if len(c2) == 1:
self.p_den += 1
self.update_b3(new_c, hypothetical=hypothetical)
if hypothetical:
f1 = evaluation.f1(self.p_num, self.p_den, self.r_num, self.r_den, beta=beta)
self.p_num, self.r_num, self.p_den, self.r_den = p_num, r_num, p_den, r_den
timer.stop("link")
return f1
else:
self.ana_to_ant[m2] = m1
self.ant_to_anas[m1].append(m2)
self.clusters.remove(c1)
self.clusters.remove(c2)
self.clusters.append(new_c)
for m in new_c:
self.mention_to_cluster[m] = new_c
timer.stop("link")
def unlink(self, m):
timer.start("unlink")
old_ant = self.ana_to_ant[m]
if old_ant != -1:
self.ana_to_ant[m] = -1
self.ant_to_anas[old_ant].remove(m)
old_c = self.mention_to_cluster[m]
c1 = [m]
frontier = self.ant_to_anas[m][:]
while len(frontier) > 0:
m = frontier.pop()
c1.append(m)
frontier += self.ant_to_anas[m]
c1 = tuple(c1)
c2 = tuple(m for m in old_c if m not in c1)
self.update_b3(c1)
self.update_b3(c2)
self.clusters.remove(old_c)
self.clusters.append(c1)
self.clusters.append(c2)
for m in c1:
self.mention_to_cluster[m] = c1
for m in c2:
self.mention_to_cluster[m] = c2
timer.stop("unlink")
def load_gold(dataset_name):
gold = {}
mention_to_gold = {}
for doc_gold in util.load_json_lines(directories.GOLD + dataset_name):
did = int(doc_gold.keys()[0])
gold[did] = doc_gold[str(did)]
mention_to_gold[did] = {}
for gold_cluster in doc_gold[str(did)]:
for m in gold_cluster:
mention_to_gold[did][m] = tuple(gold_cluster)
return gold, mention_to_gold
def load_mentions(dataset_name):
mentions = defaultdict(list)
mention_ids = np.load(directories.MENTION_DATA + dataset_name + '/mid.npy')
doc_ids = np.load(directories.MENTION_DATA + dataset_name + '/mdid.npy')
for did, mid in zip(doc_ids[:, 0], mention_ids[:, 0]):
mentions[did].append(mid)
return mentions
def write_docs(dataset_name):
gold, mention_to_gold = load_gold(dataset_name)
mentions = load_mentions(dataset_name)
docs = []
for did in gold:
docs.append(Document(did, mentions[did],
gold[did], mention_to_gold[did]))
util.write_pickle(docs, directories.DOCUMENTS + dataset_name + '_docs.pkl')
def main():
write_docs("train")
write_docs("dev")
write_docs("test")
if __name__ == '__main__':
main()