def howmuch_2(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<\$>*<CD>+<MD>?<VB|VBD|VBG|VBP|VBN|VBZ|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
list3 = []
if len(list1) != 0:
for j in range(len(list1)):
m = list1[j]
str1 = ""
for k in range(m + 1, len(chunked)):
if k in list1:
str1 += nonClause.get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
str2 = nonClause.get_chunk(chunked[m])
tok = nltk.word_tokenize(str2)
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
s11 = ' how much '
list2 = identification.chunk_search(str2, chunked1)
if len(list2) != 0:
str2 = nonClause.get_chunk(chunked1[list2[0]])
str2 = s11 + str2
for k in range(list2[0] + 1, len(chunked1)):
if k in list2:
str2 += nonClause.get_chunk(chunked[k])
else:
str2 += (chunked[k][0] + " ")
str2 += (" " + str1)
tok_1 = nltk.word_tokenize(str2)
str2 = ""
for h in range(len(tok_1)):
if tok_1[h] == "am":
str2 += " is "
else:
str2 += (tok_1[h] + " ")
for l in range(num + 1, len(segment_set)):
str2 += ("," + segment_set[l])
str2 += '?'
str2 = identification.postprocess(str2)
# str2 = 'Q.' + str2
list3.append(str2)
return list3
def howmany(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<DT>?<CD>+<RB>?<JJ|JJR|JJS>?<NN|NNS|NNP|NNPS|VBG>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
s = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str3 = ""
str2 = " how many "
if j in list1:
for k in range(j):
if k in list1:
str1 += get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
st = get_chunk(chunked[j])
tok = nltk.word_tokenize(st)
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<RB>?<JJ|JJR|JJS>?<NN|NNS|NNP|NNPS|VBG>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
list2 = identification.chunk_search(st, chunked1)
z = ""
for k in range(len(chunked1)):
if k in list2:
z += get_chunk(chunked1[k])
str4 = str1 + str2 + z + str3
for k in range(len(segment_set)):
if k != num:
str4 += ("," + segment_set[k])
str4 += '?'
str4 = identification.postprocess(str4)
# str4 = 'Q.' + str4
s.append(str4)
return s
def what_whom1(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<TO>+<DT>?<RB.?>*<JJ.?>*<NN.?|PRP|PRP\$|VBG|DT|POS|CD|VBN>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
s = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str3 = ""
if j in list1:
for k in range(j):
if k in list1:
str1 += get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
if chunked[j][1][1] == 'PRP':
str2 = "why " ##replaced
else:
for x in range(len(chunked[j])):
if (chunked[j][x][1] == "NNP"
or chunked[j][x][1] == "NNPS"
or chunked[j][x][1] == "NNS"
or chunked[j][x][1] == "NN"):
break
for x1 in range(len(ner)):
if ner[x1][0] == chunked[j][x][0]:
if ner[x1][1] == "PERSON":
str2 = " to whom "
elif ner[x1][1] == "LOC" or ner[x1][
1] == "ORG" or ner[x1][1] == "GPE":
str2 = " what caused" #replaced
elif ner[x1][1] == "TIME" or ner[x1][1] == "DATE":
str2 = " when "
else:
str2 = "to what"
str4 = str1 + str2 + str3
for k in range(len(segment_set)):
if k != num:
str4 += ("," + segment_set[k])
str4 += '?'
str4 = identification.postprocess(str4)
# str4 = 'Q.' + str4
s.append(str4)
return s
def whose(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<DT|NN.?>*<PRP\$|POS>+<RB.?>*<JJ.?>*<NN.?|VBG|VBN>+<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
list3 = []
if len(list1) != 0:
for i in range(len(chunked)):
if i in list1:
str1 = ""
str3 = ""
str2 = ""
for k in range(i):
if k in list1:
str1 += nonClause.get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
str1 += " whose "
for k in range(i + 1, len(chunked)):
if k in list1:
str3 += nonClause.get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
if chunked[i][1][1] == 'POS':
for k in range(2, len(chunked[i])):
str2 += (chunked[i][k][0] + " ")
if chunked[i][0][1] == 'PRP$':
for k in range(1, len(chunked[i])):
str2 += (chunked[i][k][0] + " ")
str2 = str1 + str2 + str3
str4 = ""
for l in range(0, len(segment_set)):
if l < num:
str4 += (segment_set[l] + ",")
if l > num:
str2 += ("," + segment_set[l])
str2 = str4 + str2
str2 += '?'
str2 = identification.postprocess(str2)
# str2 = 'Q.' + str2
list3.append(str2)
return list3
def whose(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<NN.?>*<PRP\$|POS>+<RB.?>*<JJ.?>*<NN.?|VBG|VBN>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
s = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str3 = ""
str2 = " whose "
if j in list1:
for k in range(j):
if k in list1:
str1 += get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
if chunked[j][1][1] == 'POS':
for k in range(2, len(chunked[j])):
str2 += (chunked[j][k][0] + " ")
else:
for k in range(1, len(chunked[j])):
str2 += (chunked[j][k][0] + " ")
str4 = str1 + str2 + str3
for k in range(len(segment_set)):
if k != num:
str4 += ("," + segment_set[k])
str4 += '?'
str4 = identification.postprocess(str4)
# str4 = 'Q.' + str4
s.append(str4)
return s
def howmuch_1(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<IN>+<\$>?<CD>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
s = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str3 = ""
str2 = " how much "
if j in list1:
for k in range(j):
if k in list1:
str1 += get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
str2 = chunked[j][0][0] + str2
str4 = str1 + str2 + str3
for k in range(len(segment_set)):
if k != num:
str4 += ("," + segment_set[k])
str4 += '?'
str4 = identification.postprocess(str4)
# str4 = 'Q.' + str4
s.append(str4)
return s
def whom_2(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<IN>+<DT>?<RB.?>*<JJ.?>*<NN.?|PRP|PRP\$|POS|VBG|DT|CD|VBN>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
list3 = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str2 = ""
str3 = ""
if j in list1:
for k in range(j):
if k in list1:
str1 += nonClause.get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += nonClause.get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
if chunked[j][1][1] == 'PRP':
str2 = " " + chunked[j][0][0] + " whom "
else:
for x in range(len(chunked[j])):
if (chunked[j][x][1] == "NNP"
or chunked[j][x][1] == "NNPS"
or chunked[j][x][1] == "NNS"
or chunked[j][x][1] == "NN"):
break
for x1 in range(len(ner)):
if ner[x1][0] == chunked[j][x][0]:
if ner[x1][1] == "PERSON":
str2 = " " + chunked[j][0][0] + " whom "
elif ner[x1][1] == "LOC" or ner[x1][
1] == "ORG" or ner[x1][1] == "GPE":
str2 = " where "
elif ner[x1][1] == "TIME" or ner[x1][1] == "DATE":
str2 = " when "
else:
str2 = " " + chunked[j][0][0] + " what "
tok = nltk.word_tokenize(str1)
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<EX>?<DT>?<JJ.?>*<NN.?|PRP|PRP\$|POS|IN|DT|CC|VBG|VBN>+<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
list2 = identification.chunk_search(str1, chunked1)
if len(list2) != 0:
m = list2[len(list2) - 1]
str4 = nonClause.get_chunk(chunked1[m])
str4 = identification.verbphrase_identify(str4)
str5 = ""
str6 = ""
for k in range(m):
if k in list2:
str5 += nonClause.get_chunk(chunked1[k])
else:
str5 += (chunked1[k][0] + " ")
for k in range(m + 1, len(chunked1)):
if k in list2:
str6 += nonClause.get_chunk(chunked1[k])
else:
str6 += (chunked1[k][0] + " ")
st = str5 + str2 + str4 + str6 + str3
for l in range(num + 1, len(segment_set)):
st += ("," + segment_set[l])
st += '?'
st = identification.postprocess(st)
# st = 'Q.' + st
list3.append(st)
return list3
def howmuch_3(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<MD>?<VB|VBD|VBG|VBP|VBN|VBZ>+<IN|TO>?<PRP|PRP\$|NN.?>?<\$>*<CD>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
list3 = []
if len(list1) != 0:
for j in range(len(chunked)):
str1 = ""
str2 = ""
str3 = ""
if j in list1:
for k in range(j):
if k in list1:
str1 += nonClause.get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
for k in range(j + 1, len(chunked)):
if k in list1:
str3 += nonClause.get_chunk(chunked[k])
else:
str3 += (chunked[k][0] + " ")
strx = nonClause.get_chunk(chunked[j])
tok = nltk.word_tokenize(strx)
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<MD>?<VB|VBD|VBG|VBP|VBN|VBZ>+<IN|TO>?<PRP|PRP\$|NN.?>?}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
strx = nonClause.get_chunk(chunked1[0])
str1 += (" " + strx)
str2 = ' how much '
tok = nltk.word_tokenize(str1)
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<EX>?<DT>?<JJ.?>*<NN.?|PRP|PRP\$|POS|IN|DT|CC|VBG|VBN>+<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
list2 = identification.chunk_search(str1, chunked1)
if len(list2) != 0:
m = list2[len(list2) - 1]
str4 = nonClause.get_chunk(chunked1[m])
str4 = identification.verbphrase_identify(str4)
str5 = ""
str6 = ""
for k in range(m):
if k in list2:
str5 += nonClause.get_chunk(chunked1[k])
else:
str5 += (chunked1[k][0] + " ")
for k in range(m + 1, len(chunked1)):
if k in list2:
str6 += nonClause.get_chunk(chunked1[k])
else:
str6 += (chunked1[k][0] + " ")
st = str5 + str2 + str4 + str6 + str3
for l in range(num + 1, len(segment_set)):
st += ("," + segment_set[l])
st += '?'
st = identification.postprocess(st)
# st = 'Q.' + st
list3.append(st)
return list3
def who(segment_set, num, ner):
tok = nltk.word_tokenize(segment_set[num])
tag = nltk.pos_tag(tok)
gram = r"""chunk:{<EX>?<DT>?<JJ.?>*<NN.?|PRP|PRP\$|POS|IN|DT|CC|VBG|VBN>+<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked = chunkparser.parse(tag)
list1 = identification.chunk_search(segment_set[num], chunked)
list3 = []
if len(list1) != 0:
for j in range(len(list1)):
m = list1[j]
str1 = ""
for k in range(m + 1, len(chunked)):
if k in list1:
str1 += nonClause.get_chunk(chunked[k])
else:
str1 += (chunked[k][0] + " ")
str2 = nonClause.get_chunk(chunked[m])
tok = nltk.word_tokenize(str2)
tag = nltk.pos_tag(tok)
for m11 in range(len(tag)):
if tag[m11][1] == 'NNP' or tag[m11][1] == 'NNPS' or tag[m11][
1] == 'NNS' or tag[m11][1] == 'NN':
break
s11 = ' who '
for m12 in range(len(ner)):
if ner[m12][0] == tag[m11][0]:
if ner[m12][1] == 'LOC':
s11 = ' which place '
elif ner[m12][1] == 'ORG':
s11 = ' who '
elif ner[m12][1] == 'DATE' or ner[m12][1] == 'TIME':
s11 = ' what time '
else:
s11 = ' who '
gram = r"""chunk:{<RB.?>*<VB.?|MD|RP>+}"""
chunkparser = nltk.RegexpParser(gram)
chunked1 = chunkparser.parse(tag)
list2 = identification.chunk_search(str2, chunked1)
if len(list2) != 0:
str2 = nonClause.get_chunk(chunked1[list2[0]])
str2 = s11 + str2
for k in range(list2[0] + 1, len(chunked1)):
if k in list2:
str2 += nonClause.get_chunk(chunked[k])
else:
str2 += (chunked[k][0] + " ")
str2 += (" " + str1)
tok_1 = nltk.word_tokenize(str2)
str2 = ""
for h in range(len(tok_1)):
if tok_1[h] == "am":
str2 += " is "
else:
str2 += (tok_1[h] + " ")
for l in range(num + 1, len(segment_set)):
str2 += ("," + segment_set[l])
str2 += '?'
str2 = identification.postprocess(str2)
# str2 = 'Q.' + str2
list3.append(str2)
return list3
