File size: 46,466 Bytes
2edd6d5 |
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 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 |
import copy
import re
from zipfile import ZipFile, ZIP_DEFLATED
from shutil import copy2, rmtree
import json
import os
from tqdm import tqdm
from collections import Counter
from pprint import pprint
from nltk.tokenize import TreebankWordTokenizer, PunktSentenceTokenizer
import pickle
ontology = {
"domains": { # descriptions are adapted from multiwoz22, but is_categorical may be different
"attraction": {
"description": "find an attraction",
"slots": {
"area": {
"description": "area to search for attractions",
"is_categorical": True,
"possible_values": [
"centre",
"east",
"north",
"south",
"west"
]
},
"name": {
"description": "name of the attraction",
"is_categorical": False,
"possible_values": []
},
"type": {
"description": "type of the attraction",
"is_categorical": True,
"possible_values": [
"architecture",
"boat",
"cinema",
"college",
"concerthall",
"entertainment",
"museum",
"multiple sports",
"nightclub",
"park",
"swimmingpool",
"theatre"
]
},
"entrance fee": {
"description": "how much is the entrance fee",
"is_categorical": False,
"possible_values": []
},
"open hours": {
"description": "open hours of the attraction",
"is_categorical": False,
"possible_values": []
},
"address": {
"description": "address of the attraction",
"is_categorical": False,
"possible_values": []
},
"phone": {
"description": "phone number of the attraction",
"is_categorical": False,
"possible_values": []
},
"postcode": {
"description": "postcode of the attraction",
"is_categorical": False,
"possible_values": []
},
"choice": {
"description": "number of attractions that meet the requirement",
"is_categorical": False,
"possible_values": []
}
}
},
"hotel": {
"description": "find and book a hotel",
"slots": {
"internet": {
"description": "whether the hotel has internet",
"is_categorical": True,
"possible_values": [
"free",
"no",
"yes"
]
},
"parking": {
"description": "whether the hotel has parking",
"is_categorical": True,
"possible_values": [
"free",
"no",
"yes"
]
},
"area": {
"description": "area or place of the hotel",
"is_categorical": True,
"possible_values": [
"centre",
"east",
"north",
"south",
"west"
]
},
"stars": {
"description": "star rating of the hotel",
"is_categorical": True,
"possible_values": [
"0",
"1",
"2",
"3",
"4",
"5"
]
},
"price range": {
"description": "price budget of the hotel",
"is_categorical": True,
"possible_values": [
"expensive",
"cheap",
"moderate"
]
},
"type": {
"description": "what is the type of the hotel",
"is_categorical": False,
"possible_values": [
"guesthouse",
"hotel"
]
},
"name": {
"description": "name of the hotel",
"is_categorical": False,
"possible_values": []
},
"book people": {
"description": "number of people for the hotel booking",
"is_categorical": False,
"possible_values": []
},
"book stay": {
"description": "length of stay at the hotel",
"is_categorical": False,
"possible_values": []
},
"book day": {
"description": "day of the hotel booking",
"is_categorical": True,
"possible_values": [
"monday",
"tuesday",
"wednesday",
"thursday",
"friday",
"saturday",
"sunday"
]
},
"phone": {
"description": "phone number of the hotel",
"is_categorical": False,
"possible_values": []
},
"postcode": {
"description": "postcode of the hotel",
"is_categorical": False,
"possible_values": []
},
"address": {
"description": "address of the hotel",
"is_categorical": False,
"possible_values": []
},
"ref": {
"description": "reference number of the hotel booking",
"is_categorical": False,
"possible_values": []
},
"choice": {
"description": "number of hotels that meet the requirement",
"is_categorical": False,
"possible_values": []
}
}
},
"taxi": {
"description": "rent taxi to travel",
"slots": {
"destination": {
"description": "destination of taxi",
"is_categorical": False,
"possible_values": []
},
"departure": {
"description": "departure location of taxi",
"is_categorical": False,
"possible_values": []
},
"leave at": {
"description": "leaving time of taxi",
"is_categorical": False,
"possible_values": []
},
"arrive by": {
"description": "arrival time of taxi",
"is_categorical": False,
"possible_values": []
},
"phone": {
"description": "phone number of the taxi",
"is_categorical": False,
"possible_values": []
},
"type": {
"description": "car type of the taxi",
"is_categorical": False,
"possible_values": []
}
}
},
"restaurant": {
"description": "find and book a restaurant",
"slots": {
"price range": {
"description": "price budget for the restaurant",
"is_categorical": True,
"possible_values": [
"cheap",
"expensive",
"moderate"
]
},
"area": {
"description": "area or place of the restaurant",
"is_categorical": True,
"possible_values": [
"centre",
"east",
"north",
"south",
"west"
]
},
"food": {
"description": "the cuisine of the restaurant",
"is_categorical": False,
"possible_values": []
},
"name": {
"description": "name of the restaurant",
"is_categorical": False,
"possible_values": []
},
"address": {
"description": "address of the restaurant",
"is_categorical": False,
"possible_values": []
},
"postcode": {
"description": "postcode of the restaurant",
"is_categorical": False,
"possible_values": []
},
"phone": {
"description": "phone number of the restaurant",
"is_categorical": False,
"possible_values": []
},
"book people": {
"description": "number of people for the restaurant booking",
"is_categorical": False,
"possible_values": []
},
"book time": {
"description": "time of the restaurant booking",
"is_categorical": False,
"possible_values": []
},
"book day": {
"description": "day of the restaurant booking",
"is_categorical": True,
"possible_values": [
"monday",
"tuesday",
"wednesday",
"thursday",
"friday",
"saturday",
"sunday"
]
},
"ref": {
"description": "reference number of the restaurant booking",
"is_categorical": False,
"possible_values": []
},
"choice": {
"description": "number of restaurants that meet the requirement",
"is_categorical": False,
"possible_values": []
}
}
},
"train": {
"description": "find a train to travel",
"slots": {
"destination": {
"description": "destination of the train",
"is_categorical": False,
"possible_values": []
},
"arrive by": {
"description": "arrival time of the train",
"is_categorical": False,
"possible_values": []
},
"departure": {
"description": "departure location of the train",
"is_categorical": False,
"possible_values": []
},
"leave at": {
"description": "leaving time for the train",
"is_categorical": False,
"possible_values": []
},
"duration": {
"description": "duration of the travel",
"is_categorical": False,
"possible_values": []
},
"book people": {
"description": "number of people booking for train",
"is_categorical": False,
"possible_values": []
},
"day": {
"description": "day of the train",
"is_categorical": True,
"possible_values": [
"monday",
"tuesday",
"wednesday",
"thursday",
"friday",
"saturday",
"sunday"
]
},
"ref": {
"description": "reference number of the train booking",
"is_categorical": False,
"possible_values": []
},
"price": {
"description": "price of the train ticket",
"is_categorical": False,
"possible_values": []
},
"train id": {
"description": "id of the train",
"is_categorical": False
},
"choice": {
"description": "number of trains that meet the requirement",
"is_categorical": False,
"possible_values": []
}
}
},
"police": {
"description": "find a police station for help",
"slots": {
"name": {
"description": "name of the police station",
"is_categorical": False,
"possible_values": []
},
"address": {
"description": "address of the police station",
"is_categorical": False,
"possible_values": []
},
"postcode": {
"description": "postcode of the police station",
"is_categorical": False,
"possible_values": []
},
"phone": {
"description": "phone number of the police station",
"is_categorical": False,
"possible_values": []
}
}
},
"hospital": {
"description": "find a hospital for help",
"slots": {
"department": {
"description": "specific department of the hospital",
"is_categorical": False,
"possible_values": []
},
"address": {
"description": "address of the hospital",
"is_categorical": False,
"possible_values": []
},
"phone": {
"description": "phone number of the hospital",
"is_categorical": False,
"possible_values": []
},
"postcode": {
"description": "postcode of the hospital",
"is_categorical": False,
"possible_values": []
}
}
},
"general": {
"description": "general domain without slots",
"slots": {}
}
},
"intents": {
"inform": {
"description": "inform the value of a slot"
},
"request": {
"description": "ask for the value of a slot"
},
"nobook": {
"description": "inform the user that the booking is failed"
},
"reqmore": {
"description": "ask the user for more instructions"
},
"book": {
"description": "book something for the user"
},
"bye": {
"description": "say goodbye to the user and end the conversation"
},
"thank": {
"description": "thanks for the help"
},
"welcome": {
"description": "you're welcome"
},
"greet": {
"description": "express greeting"
},
"recommend": {
"description": "recommend a choice to the user"
},
"select": {
"description": "provide several choices for the user"
},
"offerbook": {
"description": "ask the user if he or she needs booking"
},
"offerbooked": {
"description": "provide information about the booking"
},
"nooffer": {
"description": "inform the user that there is no result satisfies user requirements"
}
},
"state": {
"attraction": {
"type": "",
"name": "",
"area": ""
},
"hotel": {
"name": "",
"area": "",
"parking": "",
"price range": "",
"stars": "",
"internet": "",
"type": "",
"book stay": "",
"book day": "",
"book people": ""
},
"restaurant": {
"food": "",
"price range": "",
"name": "",
"area": "",
"book time": "",
"book day": "",
"book people": ""
},
"taxi": {
"leave at": "",
"destination": "",
"departure": "",
"arrive by": ""
},
"train": {
"leave at": "",
"destination": "",
"day": "",
"arrive by": "",
"departure": "",
"book people": ""
},
"hospital": {
"department": ""
}
},
"dialogue_acts": {
"categorical": {},
"non-categorical": {},
"binary": {}
}
}
slot_name_map = {
'addr': "address",
'post': "postcode",
'pricerange': "price range",
'arrive': "arrive by",
'arriveby': "arrive by",
'leave': "leave at",
'leaveat': "leave at",
'depart': "departure",
'dest': "destination",
'fee': "entrance fee",
'open': 'open hours',
'car': "type",
'car type': "type",
'ticket': 'price',
'trainid': 'train id',
'id': 'train id',
'people': 'book people',
'stay': 'book stay',
'none': '',
'attraction': {
'price': 'entrance fee'
},
'hospital': {},
'hotel': {
'day': 'book day', 'price': "price range"
},
'restaurant': {
'day': 'book day', 'time': 'book time', 'price': "price range"
},
'taxi': {},
'train': {
'day': 'day', 'time': "duration"
},
'police': {},
'booking': {}
}
reverse_da_slot_name_map = {
'address': 'Addr',
'postcode': 'Post',
'price range': 'Price',
'arrive by': 'Arrive',
'leave at': 'Leave',
'departure': 'Depart',
'destination': 'Dest',
'entrance fee': 'Fee',
'open hours': 'Open',
'price': 'Ticket',
'train id': 'Id',
'book people': 'People',
'book stay': 'Stay',
'book day': 'Day',
'book time': 'Time',
'duration': 'Time',
'taxi': {
'type': 'Car',
'phone': 'Phone'
}
}
digit2word = {
'0': 'zero', '1': 'one', '2': 'two', '3': 'three', '4': 'four', '5': 'five',
'6': 'six', '7': 'seven', '8': 'eight', '9': 'nine', '10': 'ten'
}
cnt_domain_slot = Counter()
class BookingActRemapper:
def __init__(self, ontology):
self.ontology = ontology
self.reset()
def reset(self):
self.current_domains_user = []
self.current_domains_system = []
self.booked_domains = []
def retrieve_current_domain_from_user(self, turn_id, ori_dialog):
prev_user_turn = ori_dialog[turn_id - 1]
dialog_acts = prev_user_turn.get('dialog_act', [])
keyword_domains_user = get_keyword_domains(prev_user_turn)
current_domains_temp = get_current_domains_from_act(dialog_acts)
self.current_domains_user = current_domains_temp if current_domains_temp else self.current_domains_user
next_user_domains = get_next_user_act_domains(ori_dialog, turn_id)
return keyword_domains_user, next_user_domains
def retrieve_current_domain_from_system(self, turn_id, ori_dialog):
system_turn = ori_dialog[turn_id]
dialog_acts = system_turn.get('dialog_act', [])
keyword_domains_system = get_keyword_domains(system_turn)
current_domains_temp = get_current_domains_from_act(dialog_acts)
self.current_domains_system = current_domains_temp if current_domains_temp else self.current_domains_system
booked_domain_current = self.check_domain_booked(system_turn)
return keyword_domains_system, booked_domain_current
def remap(self, turn_id, ori_dialog):
keyword_domains_user, next_user_domains = self.retrieve_current_domain_from_user(
turn_id, ori_dialog)
keyword_domains_system, booked_domain_current = self.retrieve_current_domain_from_system(
turn_id, ori_dialog)
# only need to remap if there is a dialog action labelled
dialog_acts = ori_dialog[turn_id].get('dialog_act', [])
spans = ori_dialog[turn_id].get('span_info', [])
if dialog_acts:
flattened_acts = flatten_acts(dialog_acts)
# flattened_spans = flatten_span_acts(spans)
remapped_acts, error_local = remap_acts(flattened_acts, self.current_domains_user,
booked_domain_current, keyword_domains_user,
keyword_domains_system, self.current_domains_system,
next_user_domains, self.ontology)
# remapped_spans, _ = remap_acts(flattened_spans, self.current_domains_user,
# booked_domain_current, keyword_domains_user,
# keyword_domains_system, self.current_domains_system,
# next_user_domains, self.ontology)
deflattened_remapped_acts = deflat_acts(remapped_acts)
# deflattened_remapped_spans = deflat_span_acts(remapped_spans)
return deflattened_remapped_acts, spans # deflattened_remapped_spans
else:
return dialog_acts, spans
def check_domain_booked(self, turn):
booked_domain_current = None
return booked_domain_current
# workaround
for domain in turn['metadata']:
if turn['metadata'][domain]["book"]["booked"] and domain not in self.booked_domains:
booked_domain_current = domain.capitalize()
self.booked_domains.append(domain)
return booked_domain_current
def get_keyword_domains(turn):
keyword_domains = []
text = turn['text']
for d in ["Hotel", "Restaurant", "Train"]:
if d.lower() in text.lower():
keyword_domains.append(d)
return keyword_domains
def get_current_domains_from_act(dialog_acts):
current_domains_temp = []
for dom_int in dialog_acts:
domain, intent = dom_int.split('-')
if domain in ["general", "Booking"]:
continue
if domain not in current_domains_temp:
current_domains_temp.append(domain)
return current_domains_temp
def get_next_user_act_domains(ori_dialog, turn_id):
domains = []
try:
next_user_act = ori_dialog[turn_id + 1]['dialog_act']
domains = get_current_domains_from_act(next_user_act)
except:
# will fail if system act is the last act of the dialogue
pass
return domains
def flatten_acts(dialog_acts):
flattened_acts = []
for dom_int in dialog_acts:
domain, intent = dom_int.split('-')
for slot_value in dialog_acts[dom_int]:
slot = slot_value[0]
value = slot_value[1]
flattened_acts.append((domain, intent, slot, value))
return flattened_acts
def flatten_span_acts(span_acts):
flattened_acts = []
for span_act in span_acts:
domain, intent = span_act[0].split("-")
flattened_acts.append((domain, intent, span_act[1], span_act[2:]))
return flattened_acts
def deflat_acts(flattened_acts):
dialog_acts = dict()
for act in flattened_acts:
domain, intent, slot, value = act
if f"{domain}-{intent}" not in dialog_acts.keys():
dialog_acts[f"{domain}-{intent}"] = [[slot, value]]
else:
dialog_acts[f"{domain}-{intent}"].append([slot, value])
return dialog_acts
def deflat_span_acts(flattened_acts):
dialog_span_acts = []
for act in flattened_acts:
domain, intent, slot, value = act
if value == 'none':
continue
new_act = [f"{domain}-{intent}", slot]
new_act.extend(value)
dialog_span_acts.append(new_act)
return dialog_span_acts
def remap_acts(flattened_acts, current_domains, booked_domain=None, keyword_domains_user=None,
keyword_domains_system=None, current_domain_system=None, next_user_domain=None, ontology=None):
# We now look for all cases that can happen: Booking domain, Booking within a domain or taxi-inform-car for booking
error = 0
remapped_acts = []
# if there is more than one current domain or none at all, we try to get booked domain differently
if len(current_domains) != 1 and booked_domain:
current_domains = [booked_domain]
elif len(current_domains) != 1 and len(keyword_domains_user) == 1:
current_domains = keyword_domains_user
elif len(current_domains) != 1 and len(keyword_domains_system) == 1:
current_domains = keyword_domains_system
elif len(current_domains) != 1 and len(current_domain_system) == 1:
current_domains = current_domain_system
elif len(current_domains) != 1 and len(next_user_domain) == 1:
current_domains = next_user_domain
for act in flattened_acts:
try:
domain, intent, slot, value = act
if f"{domain}-{intent}-{slot}" == "Booking-Book-Ref":
# We need to remap that booking act now
potential_domain = current_domains[0]
remapped_acts.append(
(potential_domain, "Book", "none", "none"))
if ontology_check(potential_domain, slot, ontology):
remapped_acts.append(
(potential_domain, "Inform", "Ref", value))
elif domain == "Booking" and intent == "Book" and slot != "Ref":
# the book intent is here actually an inform intent according to the data
potential_domain = current_domains[0]
if ontology_check(potential_domain, slot, ontology):
remapped_acts.append(
(potential_domain, "Inform", slot, value))
elif domain == "Booking" and intent == "Inform":
# the inform intent is here actually a request intent according to the data
potential_domain = current_domains[0]
if ontology_check(potential_domain, slot, ontology):
remapped_acts.append(
(potential_domain, "OfferBook", slot, value))
elif domain == "Booking" and intent in ["NoBook", "Request"]:
potential_domain = current_domains[0]
if ontology_check(potential_domain, slot, ontology):
remapped_acts.append(
(potential_domain, intent, slot, value))
elif f"{domain}-{intent}-{slot}" == "Taxi-Inform-Car":
# taxi-inform-car actually triggers the booking and informs on a car
remapped_acts.append((domain, "Book", "none", "none"))
remapped_acts.append((domain, intent, slot, value))
elif f"{domain}-{intent}-{slot}" in ["Train-Inform-Ref", "Train-OfferBooked-Ref"]:
# train-inform/offerbooked-ref actually triggers the booking and informs on the reference number
remapped_acts.append((domain, "Book", "none", "none"))
remapped_acts.append((domain, "Inform", slot, value))
elif domain == "Train" and intent == "OfferBooked" and slot != "Ref":
# this is actually an inform act
remapped_acts.append((domain, "Inform", slot, value))
else:
remapped_acts.append(act)
except Exception as e:
print("Error detected:", e)
error += 1
return remapped_acts, error
def ontology_check(domain_, slot_, init_ontology):
domain = domain_.lower()
slot = slot_.lower()
if slot not in init_ontology['domains'][domain]['slots']:
if slot in slot_name_map:
slot = slot_name_map[slot]
elif slot in slot_name_map[domain]:
slot = slot_name_map[domain][slot]
return slot in init_ontology['domains'][domain]['slots']
def reverse_da(dialogue_acts):
global reverse_da_slot_name_map
das = {}
for da_type in dialogue_acts:
for da in dialogue_acts[da_type]:
intent, domain, slot, value = da['intent'], da['domain'], da['slot'], da.get(
'value', '')
if domain == 'general':
Domain_Intent = '-'.join([domain, intent])
elif intent == 'nooffer':
Domain_Intent = '-'.join([domain.capitalize(), 'NoOffer'])
elif intent == 'nobook':
Domain_Intent = '-'.join([domain.capitalize(), 'NoBook'])
elif intent == 'offerbook':
Domain_Intent = '-'.join([domain.capitalize(), 'OfferBook'])
else:
Domain_Intent = '-'.join([domain.capitalize(),
intent.capitalize()])
das.setdefault(Domain_Intent, [])
if slot in reverse_da_slot_name_map:
Slot = reverse_da_slot_name_map[slot]
elif domain in reverse_da_slot_name_map and slot in reverse_da_slot_name_map[domain]:
Slot = reverse_da_slot_name_map[domain][slot]
else:
Slot = slot.capitalize()
if value == '':
if intent == 'request':
value = '?'
else:
value = 'none'
if Slot == '':
Slot = 'none'
das[Domain_Intent].append([Slot, value])
return das
def normalize_domain_slot_value(domain, slot, value):
global ontology, slot_name_map
domain = domain.lower()
slot = slot.lower()
value = value.strip()
if value in ['do nt care', "do n't care"]:
value = 'dontcare'
if value in ['?', 'none', 'not mentioned']:
value = ""
if domain not in ontology['domains']:
raise Exception(f'{domain} not in ontology')
if slot not in ontology['domains'][domain]['slots']:
if slot in slot_name_map:
slot = slot_name_map[slot]
elif slot in slot_name_map[domain]:
slot = slot_name_map[domain][slot]
else:
raise Exception(f'{domain}-{slot} not in ontology')
assert slot == '' or slot in ontology['domains'][domain][
'slots'], f'{(domain, slot, value)} not in ontology'
return domain, slot, value
def convert_da(da_dict, utt, sent_tokenizer, word_tokenizer):
'''
convert multiwoz dialogue acts to required format
:param da_dict: dict[(intent, domain, slot, value)] = [word_start, word_end]
:param utt: user or system utt
'''
global ontology, digit2word, cnt_domain_slot
converted_da = {
'categorical': [],
'non-categorical': [],
'binary': []
}
sentences = sent_tokenizer.tokenize(utt)
sent_spans = sent_tokenizer.span_tokenize(utt)
tokens = [
token for sent in sentences for token in word_tokenizer.tokenize(sent)]
token_spans = [(sent_span[0] + token_span[0], sent_span[0] + token_span[1]) for sent, sent_span in
zip(sentences, sent_spans) for token_span in word_tokenizer.span_tokenize(sent)]
# assert len(tokens) == len(token_spans)
# for token, span in zip(tokens, token_spans):
# if utt[span[0]:span[1]] != '"':
# assert utt[span[0]:span[1]] == token
for (intent, domain, slot, value), span in da_dict.items():
if intent == 'request' or slot == '' or value == '':
# binary dialog acts
assert value == ''
converted_da['binary'].append({
'intent': intent,
'domain': domain,
'slot': slot
})
elif ontology['domains'][domain]['slots'][slot]['is_categorical']:
# categorical dialog acts
converted_da['categorical'].append({
'intent': intent,
'domain': domain,
'slot': slot,
'value': value
})
else:
# non-categorical dialog acts
converted_da['non-categorical'].append({
'intent': intent,
'domain': domain,
'slot': slot,
'value': value
})
# correct some value and try to give char level span
match = False
value = value.lower()
if span and span[0] <= span[1]:
# use original span annotation, but tokenizations are different
start_word, end_word = span
if end_word >= len(tokens):
# due to different tokenization, sometimes will out of index
delta = end_word - len(tokens) + 1
start_word -= delta
end_word -= delta
start_char, end_char = token_spans[start_word][0], token_spans[end_word][1]
value_span = utt[start_char:end_char].lower()
match = True
if value_span == value:
cnt_domain_slot['span match'] += 1
elif value.isdigit() and value in digit2word and digit2word[value] == value_span:
# !!!CHANGE VALUE: value is digit but value span is word
cnt_domain_slot['digit value match'] += 1
elif ''.join(value.split()) == ''.join(value_span.split()):
# !!!CHANGE VALUE: equal when remove blank
cnt_domain_slot['remove blank'] += 1
elif value in value_span:
# value in value_span
start_char += value_span.index(value)
end_char = start_char + len(value)
assert utt[start_char:end_char].lower(
) == value, f'{[value, utt[start_char:end_char], utt]}'
cnt_domain_slot['value in span'] += 1
elif ':' in value and value == '0' + value_span:
# !!!CHANGE VALUE: time x:xx == 0x:xx
cnt_domain_slot['x:xx == 0x:xx'] += 1
else:
# span mismatch, search near 1-2 words
for window in range(1, 3):
start = max(0, start_word - window)
end = min(len(token_spans) - 1, end_word + window)
large_span = utt[token_spans[start]
[0]:token_spans[end][1]].lower()
if value in large_span:
start_char = token_spans[start][0] + \
large_span.index(value)
end_char = start_char + len(value)
assert utt[
start_char:end_char].lower() == value, f'{[value, utt[start_char:end_char], utt]}'
cnt_domain_slot[f'window={window}'] += 1
break
else:
# still not found
match = False
if match:
converted_da['non-categorical'][-1]['value'] = utt[start_char:end_char]
converted_da['non-categorical'][-1]['start'] = start_char
converted_da['non-categorical'][-1]['end'] = end_char
cnt_domain_slot['have span'] += 1
else:
cnt_domain_slot['no span'] += 1
return converted_da
def act_list2dict(act_list):
act_dict = {}
for intent, domain, slot, value in act_list:
key = f"{domain}-{intent}"
if key not in act_dict:
act_dict[key] = []
act_dict[key].append([slot, value])
return act_dict
def preprocess():
original_data_dir = 'emowoz'
new_data_dir = 'data'
if not os.path.exists(original_data_dir):
original_data_zip = 'MultiWOZ_2.1.zip'
if not os.path.exists(original_data_zip):
raise FileNotFoundError(
f'cannot find original data {original_data_zip} in multiwoz21/, should manually download MultiWOZ_2.1.zip from https://github.com/budzianowski/multiwoz/blob/master/data/MultiWOZ_2.1.zip')
else:
archive = ZipFile(original_data_zip)
archive.extractall()
os.makedirs(new_data_dir, exist_ok=True)
for filename in os.listdir(original_data_dir):
if 'db' in filename:
copy2(f'{original_data_dir}/{filename}', new_data_dir)
# how about emowoz-dialmage
original_data = json.load(
open(f'{original_data_dir}/emowoz-dialmage.json'))
global ontology, cnt_domain_slot
raw_data = pickle.load(open('dialog_state.pkl', 'rb'))
actions = raw_data[0]
data_split = json.load(open(f'{original_data_dir}/data_split.json'))
val_list = data_split["dev"]["dialmage"]
test_list = data_split["test"]["dialmage"]
dataset = 'emowoz-dialmage'
splits = ['train', 'validation', 'test']
dialogues_by_split = {split: [] for split in splits}
sent_tokenizer = PunktSentenceTokenizer()
word_tokenizer = TreebankWordTokenizer()
booking_remapper = BookingActRemapper(ontology)
for ori_dialog_id, ori_dialog in tqdm(original_data.items()):
act = actions[ori_dialog_id]
for turn_id in range(len(ori_dialog["log"])):
ori_dialog["log"][turn_id]["dialog_act"] = act_list2dict(
act[turn_id])
if ori_dialog_id in val_list:
split = 'validation'
elif ori_dialog_id in test_list:
split = 'test'
else:
split = 'train'
dialogue_id = f'{dataset}-{split}-{len(dialogues_by_split[split])}'
# get user goal and involved domains
cur_domains = []
dialogue = {
'dataset': dataset,
'data_split': split,
'dialogue_id': dialogue_id,
'original_id': ori_dialog_id,
'domains': cur_domains, # will be updated by dialog_acts and state
'goal': "",
'turns': []
}
booking_remapper.reset()
belief_domains = ['attraction', 'restaurant',
'train', 'hotel', 'taxi', 'hospital']
entity_booked_dict = dict((domain, False) for domain in belief_domains)
for turn_id, turn in enumerate(ori_dialog['log']):
# correct some grammar errors in the text, mainly following `tokenization.md` in MultiWOZ_2.1
text = turn['text']
text = re.sub(" Im ", " I'm ", text)
text = re.sub(" im ", " i'm ", text)
text = re.sub(r"^Im ", "I'm ", text)
text = re.sub(r"^im ", "i'm ", text)
text = re.sub("theres", "there's", text)
text = re.sub("dont", "don't", text)
text = re.sub("whats", "what's", text)
text = re.sub('thats', "that's", text)
utt = text
speaker = 'user' if turn_id % 2 == 0 else 'system'
das = turn.get('dialog_act', [])
spans = turn.get('span_info', [])
# if speaker == 'system':
das, spans = booking_remapper.remap(turn_id, ori_dialog['log'])
da_dict = {}
# transform DA
for Domain_Intent in das:
domain, intent = Domain_Intent.lower().split('-')
assert intent in ontology['intents'], f'{ori_dialog_id}:{turn_id}:da\t{intent} not in ontology'
for Slot, value in das[Domain_Intent]:
domain, slot, value = normalize_domain_slot_value(
domain, Slot, value)
if domain not in cur_domains:
# update original cur_domains
cur_domains.append(domain)
da_dict[(intent, domain, slot, value,)] = []
# for span in spans:
# Domain_Intent, Slot, value, start_word, end_word = span
# domain, intent = Domain_Intent.lower().split('-')
# domain, slot, value = normalize_domain_slot_value(
# domain, Slot, value)
# print(da_dict)
# assert (intent, domain, slot, value,) in da_dict
# da_dict[(intent, domain, slot, value,)] = [
# start_word, end_word]
dialogue_acts = convert_da(
da_dict, utt, sent_tokenizer, word_tokenizer)
# reverse_das = reverse_da(dialogue_acts)
# das_list = sorted([(Domain_Intent, Slot, ''.join(value.split()).lower()) for Domain_Intent in das for Slot, value in das[Domain_Intent]])
# reverse_das_list = sorted([(Domain_Intent, Slot, ''.join(value.split()).lower()) for Domain_Intent in reverse_das for Slot, value in reverse_das[Domain_Intent]])
# if das_list != reverse_das_list:
# print(das_list)
# print(reverse_das_list)
# print()
# print()
dialogue['turns'].append({
'speaker': speaker,
'utterance': utt,
'utt_idx': turn_id,
'dialogue_acts': dialogue_acts,
'emotion': turn['emotion']
})
# add to dialogue_acts dictionary in the ontology
for da_type in dialogue_acts:
das = dialogue_acts[da_type]
for da in das:
ontology["dialogue_acts"][da_type].setdefault(
(da['intent'], da['domain'], da['slot']), {})
ontology["dialogue_acts"][da_type][(
da['intent'], da['domain'], da['slot'])][speaker] = True
if speaker == 'system':
# add state to last user turn
# add empty db_results
# turn_state = turn['metadata']
cur_state = copy.deepcopy(ontology['state'])
booked = {}
# for domain in turn_state:
# if domain not in cur_state:
# continue
# for subdomain in ['semi', 'book']:
# for slot, value in turn_state[domain][subdomain].items():
# if slot == 'ticket':
# continue
# elif slot == 'booked':
# assert domain in ontology['domains']
# booked[domain] = value
# continue
# _, slot, value = normalize_domain_slot_value(
# domain, slot, value)
# cur_state[domain][slot] = value
dialogue['turns'][-2]['state'] = cur_state
# entity_booked_dict, booked = fix_entity_booked_info(
# entity_booked_dict, booked)
dialogue['turns'][-1]['booked'] = booked
dialogues_by_split[split].append(dialogue)
# pprint(cnt_domain_slot.most_common())
dialogues = []
for split in splits:
dialogues += dialogues_by_split[split]
for da_type in ontology['dialogue_acts']:
ontology["dialogue_acts"][da_type] = sorted([str(
{'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent': da[0],
'domain': da[1], 'slot': da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()])
json.dump(dialogues[:10], open(f'dummy_data.json', 'w',
encoding='utf-8'), indent=2, ensure_ascii=False)
json.dump(ontology, open(f'{new_data_dir}/ontology.json',
'w', encoding='utf-8'), indent=2, ensure_ascii=False)
json.dump(dialogues, open(f'{new_data_dir}/dialogues.json',
'w', encoding='utf-8'), indent=2, ensure_ascii=False)
with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf:
for filename in os.listdir(new_data_dir):
zf.write(f'{new_data_dir}/{filename}')
# rmtree(original_data_dir)
# rmtree(new_data_dir)
return dialogues, ontology
def fix_entity_booked_info(entity_booked_dict, booked):
for domain in entity_booked_dict:
if not entity_booked_dict[domain] and booked[domain]:
entity_booked_dict[domain] = True
booked[domain] = []
return entity_booked_dict, booked
if __name__ == '__main__':
preprocess()
|