File size: 82,920 Bytes
6fa4bc9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
{
    "paper_id": "2021",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T07:33:25.693800Z"
    },
    "title": "A 3 C: Arabic Anaphora Annotated Corpus",
    "authors": [
        {
            "first": "Abdelhalim",
            "middle": [
                "Hafedh"
            ],
            "last": "Dahou",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Ahmed Draia University Adrar",
                "location": {
                    "country": "Algeria"
                }
            },
            "email": ""
        },
        {
            "first": "Mohamed",
            "middle": [],
            "last": "Abdelmoazz",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Ahmed Draia University Adrar",
                "location": {
                    "country": "Algeria"
                }
            },
            "email": "m.abdelmoazz@yahoo.com"
        },
        {
            "first": "Mohamed",
            "middle": [
                "Amine"
            ],
            "last": "Cheragui",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "Ahmed Draia University Adrar",
                "location": {
                    "country": "Algeria"
                }
            },
            "email": "m_cheragui@univ-adrar.edu.dz"
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "In this paper, we describe the different steps taken to build our annotated corpus which aims to treat a known linguistic phenomenon in Arabic texts called Anaphora. The objective behind the creation of this corpus 1 is to fill the lack of resources concerning the resolution anaphora (especially pronominal and verbal) in the Modern Standard Arabic language and this is by creating a newly annotated corpus that we have called A 3 C which contains the anaphoric relations. To satisfy this objective, we created A 3 T, an anaphoric annotating tool that uses linguistic and statistical rules to automatically detect anaphors and their referents. After that, we resort to human specialists to verify and correct our A 3 T annotation's errors for the corpus's credibility. This study discusses novel features that can aid in determining the best reference, as well as the problem of the lack of resources for verbal anaphora. 2 Varieties of Anaphora in Arabic text What makes the anaphora resolution mechanism complex in natural language processing in general and in Arabic, in particular, is the fact that it can",
    "pdf_parse": {
        "paper_id": "2021",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "In this paper, we describe the different steps taken to build our annotated corpus which aims to treat a known linguistic phenomenon in Arabic texts called Anaphora. The objective behind the creation of this corpus 1 is to fill the lack of resources concerning the resolution anaphora (especially pronominal and verbal) in the Modern Standard Arabic language and this is by creating a newly annotated corpus that we have called A 3 C which contains the anaphoric relations. To satisfy this objective, we created A 3 T, an anaphoric annotating tool that uses linguistic and statistical rules to automatically detect anaphors and their referents. After that, we resort to human specialists to verify and correct our A 3 T annotation's errors for the corpus's credibility. This study discusses novel features that can aid in determining the best reference, as well as the problem of the lack of resources for verbal anaphora. 2 Varieties of Anaphora in Arabic text What makes the anaphora resolution mechanism complex in natural language processing in general and in Arabic, in particular, is the fact that it can",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "A corpus is considered today as a fundamental piece in natural language processing, due to the role that it plays in both the resolution and the testing phases. The building of annotated corpus in terms of number and size has known a real ascension in the last decades, in particular since the appearance of statistical and machine learning approaches (Beseiso and Al-Alwani, 2016), allowing, from textual resources, the development of resolution models for different linguistic phenomena such as anaphora.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": "1"
            },
            {
                "text": "Anaphora is typically defined as references to items mentioned earlier in a discourse or \"pointing back \" reference as described by (Mitkov, 99) . In addition, the process of determining the referent of an anaphora and establishing the relationship between them is known as anaphora resolution. Anaphora still a very challenging linguistic phenomenon, where its identification and resolution can increase the performance of several NLP applications, such as: sentiment analysis (Cambria, 2016) , question-answer systems (El-Said Nada et al., 2018) , machine translation (Madhura and Satish, 2019), text summarization (Antunes et al., 2018) , information extraction (Matysiak, 2007) , language generation and dialog systems (Vinay et al., 2019) .",
                "cite_spans": [
                    {
                        "start": 132,
                        "end": 140,
                        "text": "(Mitkov,",
                        "ref_id": null
                    },
                    {
                        "start": 141,
                        "end": 144,
                        "text": "99)",
                        "ref_id": null
                    },
                    {
                        "start": 478,
                        "end": 493,
                        "text": "(Cambria, 2016)",
                        "ref_id": "BIBREF5"
                    },
                    {
                        "start": 520,
                        "end": 547,
                        "text": "(El-Said Nada et al., 2018)",
                        "ref_id": null
                    },
                    {
                        "start": 617,
                        "end": 639,
                        "text": "(Antunes et al., 2018)",
                        "ref_id": "BIBREF1"
                    },
                    {
                        "start": 665,
                        "end": 681,
                        "text": "(Matysiak, 2007)",
                        "ref_id": "BIBREF16"
                    },
                    {
                        "start": 723,
                        "end": 743,
                        "text": "(Vinay et al., 2019)",
                        "ref_id": "BIBREF27"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": "1"
            },
            {
                "text": "Our motivation behind this work is to enhance anaphora resolution in Arabic text by building an anaphoric annotated corpus that can contribute to future works that tackle anaphora in the Arabic language.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": "1"
            },
            {
                "text": "This paper is structured in 6 sections. Section 2, describe the anaphoric typology in Arabic language. Section 3, gives an overview of existing anaphoric corpora (case of Arabic). Section 4, presents the challenges we face in Arabic anaphora resolution. Section 5, outlines the different phases of building of our A 3 C corpus. Section 6, some observations noted during the building process of our corpus. The last section gives a conclusion and future work. manifest in different forms (linguistic categories: lexical and grammatical), but also requires knowledge at different levels, as well as an \"understanding\" of the context. There are many varieties of anaphora in the Arabic text, we will only mention the most frequent ones.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Introduction",
                "sec_num": "1"
            },
            {
                "text": "Verbal anaphora is used to describe or represent various movements or actions by using the verb (did -\u202b\u0641\u0639\u0644\u202c -) and the different conjugation variants to minimize writing and avoid repetition (Trabelsi et al., 2016; Hamouda, 2014) . ",
                "cite_spans": [
                    {
                        "start": 191,
                        "end": 214,
                        "text": "(Trabelsi et al., 2016;",
                        "ref_id": "BIBREF26"
                    },
                    {
                        "start": 215,
                        "end": 229,
                        "text": "Hamouda, 2014)",
                        "ref_id": "BIBREF11"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Verbal anaphora",
                "sec_num": "2.1"
            },
            {
                "text": "Lexical anaphora occurs when the referent is designated by definite descriptions representing the same concept (the anaphora), or concepts that are semantically close (Hammami, 2009) . Usually, this form of anaphora adds more information to the sentence and increases cohesion, and can take several forms (synonym, generalization / hypernymy, or specialization /hyponymy) (Seddik and Farghaly, 2014). ",
                "cite_spans": [
                    {
                        "start": 167,
                        "end": 182,
                        "text": "(Hammami, 2009)",
                        "ref_id": "BIBREF10"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Lexical anaphora",
                "sec_num": "2.2"
            },
            {
                "text": "This type of anaphora is manifested by the introduction of lexical modifiers (e.g., \u202b\u0623\u062e\u0631\u202c / other, \u202b\u0623\u062e\u0631\u0649\u202c / one, \u202b)\u0648\u062d\u062f\u0629\u202c or comparative adjectives ( \u202b\u0645\u0646\u202c \u202b\u0623\u0643\u0628\u0631\u202c / greater than , \u202b\u0645\u0646\u202c \u202b\u0623\u062d\u0633\u0646\u202c / better than) (Hammami, 2009) . This variety of anaphora indicates a relation like: such as set-complement, similarity and comparison between the anaphora and the referent (Mahmoud Seddik and Farghaly, 2014). ",
                "cite_spans": [
                    {
                        "start": 205,
                        "end": 220,
                        "text": "(Hammami, 2009)",
                        "ref_id": "BIBREF10"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Comparative anaphora",
                "sec_num": "2.3"
            },
            {
                "text": "Based on statistical studies done by (Hammami, 2009) it shows that the pronominal anaphora is the most frequent variant in Arabic texts. Pronouns form a special class of an\"aphora because of their empty semantic structures; they have a meaning independent of its referents and usually refer to names or noun phrases (Beseiso and Al-Alwani, 2016). However, not all pronouns are anaphoric.",
                "cite_spans": [
                    {
                        "start": 37,
                        "end": 52,
                        "text": "(Hammami, 2009)",
                        "ref_id": "BIBREF10"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Pronominal anaphora",
                "sec_num": "2.4"
            },
            {
                "text": "Pronominal Anaphors can be divided into three categories, each category can be subdivided into subcategories according to several parameters, such as gender, number, etc.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Pronominal anaphora",
                "sec_num": "2.4"
            },
            {
                "text": "3 rd personal pronouns ( \u202b\u0627\u0644\u063a\u0627\u0626\u0628\u202c \u202b:)\u0636\u0645\u0627\u0626\u0631\u202c In the Arabic, not all personal pronouns are anaphoric, so the 1 st person ( \u202b\u0646\u062d\u0646\u202c \u202b\u0648\u202c \u202b)\u0627\u0646\u0627\u202c and 2 nd person ( \u202b\u0627\u0646\u062a\u0645\u0627\u202c \u202b\u0623\u0646\u062a\u202c .., etc.) pronouns are not (they specify the communication partners and their meaning goes back to their specific uses), except the 3 rd person pronouns which have this characteristic. These pronouns can be subdivided into two categories: disjoint pronoun (Example: \u202b\u0647\u064a\u202c / she \u202b\u0647\u0648\u202c \u060c / he) and joint pronoun (Example: ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Pronominal anaphora",
                "sec_num": "2.4"
            },
            {
                "text": "\u202b\u0640\u0647\u202c \u060c \u202b\u0627\u202c \u060c \u202b\u0646\u202c ) (El-Said",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Pronominal anaphora",
                "sec_num": "2.4"
            },
            {
                "text": "Translation: \"Soumaia has sewn her sister's wedding dress and she is very excited\". In some cases the pronouns \" \u202b\"\u0640\u0647\u202c and \" \u202b\"\u0640\u0647\u0627\u202c are not anaphoric since they are not interpreted as related to an expression (referent). In this case we will call them pleonastic pronouns. The use of relative pronouns is possible if the referent denotes a process or situation, and here the anaphora denotes some of these lexical meanings. They refer to persons, places or things that are close or distant, the table below illustrates this type of pronouns.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Disjoint Personal Pronoun Anaphora",
                "sec_num": null
            },
            {
                "text": "Demonstrative pronouns ( \u202b\u0623\u0633\u0645\u202c \u202b\u0627\u0625\u0644\u0634\u0627\u0631\u0629\u202c \u202b\u0627\u0621\u202c ): They are linguistic elements that accompany a designation gesture in order to coordinate the attention of the interlocutors when they are speaking (Jarbou, 2018). Generally, demonstrative pronouns are cataphoric and in some cases they can be anaphoric and even deixis (Bouzid et al., 2014) . Demonstratives agree in person, gender and number with their referent. In addition, there are pronouns, which are considered demonstratives, and which designate time and place (Example: \u202b\u0647\u0630\u0627\u202c / this, \u202b\u0647\u0646\u0627\u202c / here). ",
                "cite_spans": [
                    {
                        "start": 317,
                        "end": 338,
                        "text": "(Bouzid et al., 2014)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Disjoint Personal Pronoun Anaphora",
                "sec_num": null
            },
            {
                "text": "For Arabic language, a considerable effort has been made concerning the anaphoric phenomenon during the last two decades, which is reflected by several studies aiming in their majority to solve the problem of the pronominal anaphora. The objective of this section is to present an overview of works dedicated to building annotated corpus (anaphora identification and referent determination).",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Related Work",
                "sec_num": "3"
            },
            {
                "text": "AnATAr (Hammami, 2009) 18895 words 2722 pairs of anaphor /referent. ",
                "cite_spans": [
                    {
                        "start": 7,
                        "end": 22,
                        "text": "(Hammami, 2009)",
                        "ref_id": "BIBREF10"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Anaphoric Resolution Category",
                "sec_num": null
            },
            {
                "text": "The aim of this section is to present the main factors, which affect anaphoric resolution.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Ambiguities and anaphoric resolution",
                "sec_num": "4"
            },
            {
                "text": "Without diacritics marks, an Arabic text is extremely unclear (morphologically and grammatically). According to (Debili and Achour, 1998), 74% of Arabic words might potentially take several lexical diacritization, making it difficult to determine if the anaphoric phenomenon or referent is the case. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Ambiguities and lack of diacritics",
                "sec_num": "4.1"
            },
            {
                "text": "Translation: \"I know the student who went to China\". ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Relative Pronoun Anaphora",
                "sec_num": null
            },
            {
                "text": "The Arabic script is characterized by the agglutination phenomena, which is explained by the fact of combining numbers of words in just one. Compared to French or English, an Arabic word can sometimes correspond to a full sentence (Bouzida and Zribi, 2020). ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Agglutination phenomenon",
                "sec_num": "4.2"
            },
            {
                "text": "Arabic is a nearly free-order language. This order causes artificial syntactic ambiguities, since the grammar should provide all the possible combination rules for reversing the order of words in the sentence. For anaphora resolution, this type of flexibility is a problem for referent localization (Beseiso and Al-Alwani, 2016; Fotiadou et al., 2020). ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Syntactic flexibility (Words free order)",
                "sec_num": "4.3"
            },
            {
                "text": "This difficulty occurs when the referent is ambiguous (due to the presence of two or more referents for the same anaphora). In this case, external knowledge of the context is necessary to identify the correct referent (Brunner et al., 2002 ).",
                "cite_spans": [
                    {
                        "start": 218,
                        "end": 239,
                        "text": "(Brunner et al., 2002",
                        "ref_id": "BIBREF2"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Ambiguity of the referent",
                "sec_num": "4.4"
            },
            {
                "text": "2 Joint Personal Pronoun \u00ab \u202b\u0647\u202c \u00bb are anaphoric. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Ambiguity of the referent",
                "sec_num": "4.4"
            },
            {
                "text": "This case occurs when the anaphora refers to something, which is not present in the sentence or text. The Qur'anic text is an example where this phenomenon persists (Seddik and Farghaly, 2011), so in the example below the pronominal anaphora ( \u202b\u0647\u0648\u202c / he) refers to ( \u202b\u0644\u0644\u0627\u202c /Allah) which is not present in the \"Aya\". The human through his knowledge and reasoning system can easily make the connection between the pronominal anaphora ( \u202b\u0647\u0648\u202c / he) and ( \u202b\u0644\u0644\u0627\u202c /Allah). However, for anaphoric resolution systems the task is complicated. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Hidden referent",
                "sec_num": "4.5"
            },
            {
                "text": "As mentioned above, the main objective is to provide an annotated resource that can be used in the automatic Arabic anaphora resolving systems. We decided to create an operational tool with a friendly interface that would help computer scientists and linguists to develop such resources. In this section, we'll go over the steps involved in building our corpus A 3 C and annotating it with our A 3 T system. We thought about breaking down the creation of our work environment into three Translation: \"And to Him belongs that which reposes by night and by day, and He is the Hearing, the Knowing.\"( Surah Al-An'\u0101m -13) (03) phases: data collection, anaphora resolution system, corpus annotation and verification. Each phase consists of essential modules that take place to accomplish the phase's purpose. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Building the A3 C",
                "sec_num": "5"
            },
            {
                "text": "Our purpose is to build a corpus of texts from different fields to cover two types of anaphora, pronominal and verbal anaphora. The texts in our corpus are taken from the Alriyadh newspaper 4 , a daily Arabic newspaper, and they are divided into five categories: culture, sports, politics, economy, and miscellaneous. The choice of those categories is made after an analysis of different categories of texts in terms of the number and diversity of anaphora types. On the other hand, the choice of this newspaper is due to the volume of information, good structure of articles and diversity of categories. To attend to this objective, we developed a crawler system that takes as an input the URL of the category page and the limited number of articles, then returns as an output a cleaned text file in (.txt) format.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Data collection",
                "sec_num": "5.1"
            },
            {
                "text": "We all know how effort and time consuming it is to manually resolve anaphora and annotate a text corpus. As a result, we created the A3T (Arabic Anaphora Annotating Program), a tool that manages resolution and annotation in an automatic way, while also providing a user-friendly interface to modify the results. The resolution process was divided into two sub-modules:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Co-reference Resolution",
                "sec_num": "5.2"
            },
            {
                "text": "Data Preparation: To help us address the anaphora problem, the text corpus must go through three processes. The first step is to break each text file into sentences using a sentence splitter mechanism based on the punctuations. Secondly, organizing these sentences in a specific input structure to prepare them for the POS and morphological analysis (Figure 11 ). Finally, determine which grammatical category a given word belongs to and other morphological features such as gender, number, state, voice. The MADAMIDA tool was chosen for our purposes because of its 95.9% precision and high-quality word-level disambiguation as mentioned in (Pasha et al., 2014) . The word-level disambiguation functionality will help us in the identification of the attached pronouns. Anaphora Resolution System: A 3 T allows the expert to select text to automatically detect and resolve anaphora. Once selected, the following three steps are applied to detect and resolve the problem :",
                "cite_spans": [
                    {
                        "start": 641,
                        "end": 661,
                        "text": "(Pasha et al., 2014)",
                        "ref_id": "BIBREF19"
                    }
                ],
                "ref_spans": [
                    {
                        "start": 350,
                        "end": 360,
                        "text": "(Figure 11",
                        "ref_id": "FIGREF0"
                    }
                ],
                "eq_spans": [],
                "section": "Co-reference Resolution",
                "sec_num": "5.2"
            },
            {
                "text": "\u2022 Anaphora identification: Anaphora is identified by referring to their grammatical code, which is based on the MADAMIRA tag set. The output here is a list of all anaphora in the text with additional information like Id, Name, Gender, Number, and Sentence number. For the pronominal anaphora, the process differs from one type to another, for example, the POS tagging for pronominal attached anaphora doesn't have a tag for gender, number, and person because the output is in the attached form, we should apply a split mechanism to place each of them in their proper tag as illustrated in (Figure 13 ). On the other hand, for verbal anaphora identification, we combine all of the elements used for pronominal anaphora identification, such as gender, number, and so on, with a new feature that will aid in the resolution which is the voice feature (active or passive form). Tables 4 and 5 illustrate the distribution of the various types of anaphora in our corpus after applying this process. Table 4 : Statistics about the A 3 C corpus (A).",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 589,
                        "end": 599,
                        "text": "(Figure 13",
                        "ref_id": "FIGREF0"
                    },
                    {
                        "start": 992,
                        "end": 999,
                        "text": "Table 4",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Co-reference Resolution",
                "sec_num": "5.2"
            },
            {
                "text": "Economy 1455",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Category Verbal Anaphora",
                "sec_num": null
            },
            {
                "text": "Education 1294",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Category Verbal Anaphora",
                "sec_num": null
            },
            {
                "text": "Politics 924",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Category Verbal Anaphora",
                "sec_num": null
            },
            {
                "text": "Miscellany 1932 Table 5 : Statistics about the A 3 C corpus (B).",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 16,
                        "end": 23,
                        "text": "Table 5",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Sport 1370",
                "sec_num": null
            },
            {
                "text": "5 Pro. Ana: Pronominal Anaphora Figure 13 : Example of pronominal anaphora identification",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 32,
                        "end": 41,
                        "text": "Figure 13",
                        "ref_id": "FIGREF0"
                    }
                ],
                "eq_spans": [],
                "section": "Sport 1370",
                "sec_num": null
            },
            {
                "text": "\u2022 Identification of referent candidates: Referents are chosen based on their POS (nouns, NPs and proper noun) and a specific search scope is adjusted based on some tests and previous research (Mitkov, 99). The search scope is still not fixed in the case of anaphora, but based on analysis, a high number of references occurs on the two previous sentences. In our case, we took two sentences before and as a special case for the demonstrative anaphora, we took the same number after. For the case of verbal anaphora, in the active form, we took two sentences after the verb and for the passive or unknown form; we took two sentences before the verb. The selection considers all of a candidate's features, including gender, number, voice, definiteness, and sentence number.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Sport 1370",
                "sec_num": null
            },
            {
                "text": "\u2022 Anaphora resolving: The goal is to choose the most appropriate referents from among the most likely candidates for each anaphora. We used morphological filters to remove unsuitable candidates by comparing gender, number, and existing sentence (search scope). To find the suitable referent, we used a collection of preferential factors that favor certain candidates over others, as shown in Table 6 . Each rule has a score that is fixed after a series of experiments that took into account previous work (Abolohom and Omar, 2017) . Each candidate was given a score for each rule, and the one with the highest overall score was recommended as Pronominal Anaphora <tok id=\"2\" form0 \u202b\"\u0647+\"=\u202c form1=\"+POSS_PRON_3MS\"/> the best referent. We chose the one that came closest to overcoming the score similarity.",
                "cite_spans": [
                    {
                        "start": 505,
                        "end": 530,
                        "text": "(Abolohom and Omar, 2017)",
                        "ref_id": "BIBREF0"
                    }
                ],
                "ref_spans": [
                    {
                        "start": 392,
                        "end": 399,
                        "text": "Table 6",
                        "ref_id": "TABREF10"
                    }
                ],
                "eq_spans": [],
                "section": "Sport 1370",
                "sec_num": null
            },
            {
                "text": "Description A score of 1 is given if an NP is definite and of 0 if not.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Linguistic rules Description",
                "sec_num": null
            },
            {
                "text": "A score of 1 is assigned to the recency (nearest one) NP to the anaphora and 0 if not.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Recency",
                "sec_num": null
            },
            {
                "text": "A score of 2 is assigned to NPs in the previous sentence or two sentences and further than those are given 0.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Referential Distance",
                "sec_num": null
            },
            {
                "text": "A score of 1 is issued to the first NP of each sentence and 0 if not.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "First Noun Phrases",
                "sec_num": null
            },
            {
                "text": "A score of 1 is issued to the existing NP in title and 0 if not",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "NPs in the title",
                "sec_num": null
            },
            {
                "text": "Scores of 1 are given to an NP that has the same morpho-syntactic features as the anaphora and 0 if not.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Grammatical function",
                "sec_num": null
            },
            {
                "text": "A score of 2 is assigned to the most frequent NP in text and 0 if not. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Frequency of NP in text",
                "sec_num": null
            },
            {
                "text": "This phase aims to annotate the text document using the obtained information from the previous phase, which is a list of pairs of anaphora and their appropriate referent, along with features like Gender, Number, Type, and POS. We used our tool A 3 T to make the annotation process simpler and fast. The tool offers a user-friendly interface to linguistic experts, allowing them to check and, if possible, change the connections between anaphora and its referent, resulting in a reliable corpus that can be used in other studies.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus annotation and verification",
                "sec_num": "5.3"
            },
            {
                "text": "More specifically, the interface displays the annotated text in the center, while all of the couples anaphora/candidates are displayed on the right, with the system's chosen couple.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus annotation and verification",
                "sec_num": "5.3"
            },
            {
                "text": "In this case, all the expert has to do is check whether the anaphora tag's number of referent matches the correct one, if not, he may adjust the number of referent to the correct one from the other suggested couples or create a new one if the system doesn't find out the correct antecedent.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Corpus annotation and verification",
                "sec_num": "5.3"
            },
            {
                "text": "In the final part, the tool will add automatically the following tags for the referent and the anaphora: the first will be marked with the <Referent> tag. The remaining elements (anaphora) will be marked with <Anaphor >. We also include the features listed above in each referent and anaphora tag. Finally, the A 3 T will generate an XML file that contains the text with anaphoric relationship tags as shown in Figure 15 . ",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 411,
                        "end": 420,
                        "text": "Figure 15",
                        "ref_id": "FIGREF0"
                    }
                ],
                "eq_spans": [],
                "section": "Corpus annotation and verification",
                "sec_num": "5.3"
            },
            {
                "text": "In our A 3 T system's testing, we used the \"AnATAr\" corpora for the evaluation for both anaphora phenomena. We used the standard accuracy metric to calculate the efficiency of the A 3 T and Table 7 presents the results obtained. We were unaware of any prior works on verbal anaphora, so we tested our work by taking the help of a linguistics specialist and utilizing the same corpora.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 190,
                        "end": 197,
                        "text": "Table 7",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "Results and Discussion",
                "sec_num": "6"
            },
            {
                "text": "Pronominal anaphora",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Anaphora Type Corpus Accuracy achieved",
                "sec_num": null
            },
            {
                "text": "Verbal anaphora AnATAr 57.23% Table 7 : The result of anaphora resolution system A 3 T on AnATAr corpora",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 30,
                        "end": 37,
                        "text": "Table 7",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "83.19%",
                "sec_num": null
            },
            {
                "text": "After analyzing the output of our system, particularly for the verbal anaphora, we found some factors that have influenced our findings. The first factor is the word disambiguation tool limitation that can't in some cases specify the correct meaning of a word such as \" \u202b\"\u0633\u0645\u0648\u0647\u202c which can act as verb (name; designate) and noun (Highness; grace) or \" \u202b\"\u0627\u062e\u0627\u0647\u202c (brother, fraternize). The second factor is the search scope, which could also lead to the best referent being excluded from the list of referents due to being out of scope. In the automatic resolution, the tool rid the references that span multiple sentences but we correct this issue in the expert verification part. The third factor is that the MADAMIRA tool can't recognize composed words like \" \u202b\u0627\u0644\u0639\u0631\u0628\u064a\u0629\u202c \u202b\u0645\u0635\u0631\u202c \u202b\"\u062c\u0645\u0647\u0648\u0631\u064a\u0629\u202c (Arab Republic of Egypt) or even compound proper names that always occur together like \" \u202b\u0645\u062d\u0645\u202c \u202b\u0635\u0627\u0644\u062d\u202c \u202b\u062f\u202c \" (Mohamed Salah). Finally, in some situations, the voice feature causes a faulty judgment when deciding if the better referent occurs before or after the verb anaphora.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "83.19%",
                "sec_num": null
            },
            {
                "text": "Anaphora plays an important role in understanding text and making it coherent. At the same time, it is still a challenging task in the Arabic language due to the complexity of language, the low number of tools, and the lack of linguistic resources. Our present work will make a contribution in the field of linguistic resources for anaphora in the Arabic language and that by providing an annotated corpus that takes into consideration the pronominal and the verbal type. In terms of reducing effort and time consuming during the phase of resolution and annotating, we created A 3 T, a tool that uses linguistic concepts to identify this phenomenon. With the help of the expert, we are sure that the A 3 C will be very useful to use in terms of developing intelligence tools that tackle the Arabic anaphora. For the perspectives, our vision will concentrate on the amelioration of the verbal resolution mechanism by using state-of-the-art tools and methods in computational linguistics and at the same time increase the size of the A 3 C corpus.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Conclusion",
                "sec_num": "7"
            },
            {
                "text": "The Corpus is available for the community in : https://dahouabdelhalim.github.io/Anaphora-Corpus/",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            },
            {
                "text": "https://www.alriyadh.com/",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "",
                "sec_num": null
            }
        ],
        "back_matter": [],
        "bib_entries": {
            "BIBREF0": {
                "ref_id": "b0",
                "title": "A Computational Model for Resolving Arabic Anaphora using Linguistic Criteria",
                "authors": [
                    {
                        "first": "Abolohom",
                        "middle": [],
                        "last": "Abdullatif",
                        "suffix": ""
                    },
                    {
                        "first": "Omar",
                        "middle": [],
                        "last": "Nazlia",
                        "suffix": ""
                    }
                ],
                "year": 2017,
                "venue": "Indian Journal of Science and Technology",
                "volume": "10",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Abolohom Abdullatif and Omar Nazlia. 2017. A Computational Model for Resolving Arabic Anaphora using Linguistic Criteria. Indian Journal of Science and Technology. Volume 10. Issue 3.",
                "links": null
            },
            "BIBREF1": {
                "ref_id": "b1",
                "title": "Automatic cohesive summarization with pronominal anaphora resolution",
                "authors": [
                    {
                        "first": "Antunes",
                        "middle": [],
                        "last": "Jamilson",
                        "suffix": ""
                    },
                    {
                        "first": "Dueire Lins",
                        "middle": [],
                        "last": "Rafael",
                        "suffix": ""
                    },
                    {
                        "first": "Lima",
                        "middle": [],
                        "last": "Rinaldo",
                        "suffix": ""
                    },
                    {
                        "first": "Oliveira",
                        "middle": [],
                        "last": "Hil\u00e1rio",
                        "suffix": ""
                    },
                    {
                        "first": "Riss",
                        "middle": [],
                        "last": "Marcelo",
                        "suffix": ""
                    },
                    {
                        "first": "Simske",
                        "middle": [],
                        "last": "Steven",
                        "suffix": ""
                    }
                ],
                "year": 2018,
                "venue": "Computer Speech & Language",
                "volume": "52",
                "issue": "",
                "pages": "141--164",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Antunes Jamilson , Dueire Lins Rafael , Lima Rinaldo , Oliveira Hil\u00e1rio , Riss Marcelo , Simske Steven. 2018. Automatic cohesive summarization with pronominal anaphora resolution. Computer Speech & Language. Volume 52, page (s) 141-164.",
                "links": null
            },
            "BIBREF2": {
                "ref_id": "b2",
                "title": "Pronominal Anaphora Resolution in the KANTOO Multilingual Machine Translation System. Language Technologies Institute",
                "authors": [
                    {
                        "first": "",
                        "middle": [],
                        "last": "Baker Kathryn",
                        "suffix": ""
                    },
                    {
                        "first": "Mitamura",
                        "middle": [],
                        "last": "Brunner Annelen",
                        "suffix": ""
                    },
                    {
                        "first": "Nyberg",
                        "middle": [],
                        "last": "Teruko",
                        "suffix": ""
                    },
                    {
                        "first": "Svoboda",
                        "middle": [],
                        "last": "Eric",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Dave",
                        "suffix": ""
                    },
                    {
                        "first": "Enrique",
                        "middle": [],
                        "last": "Torrejon",
                        "suffix": ""
                    }
                ],
                "year": 2002,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Baker Kathryn, Brunner Annelen, Mitamura Teruko, Nyberg Eric, Svoboda Dave and Torrejon, Enrique. 2002. Pronominal Anaphora Resolution in the KANTOO Multilingual Machine Translation System. Language Technologies Institute, Carnegie Mellon University.",
                "links": null
            },
            "BIBREF3": {
                "ref_id": "b3",
                "title": "A Coreference Resolution Approach using Morphological Features in Arabic",
                "authors": [
                    {
                        "first": "Beseiso",
                        "middle": [],
                        "last": "Majdi",
                        "suffix": ""
                    },
                    {
                        "first": "Al-Alwani",
                        "middle": [],
                        "last": "Abdulkareem",
                        "suffix": ""
                    }
                ],
                "year": 2016,
                "venue": "International Journal of Advanced Computer Science and Applications",
                "volume": "7",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Beseiso Majdi and Al-Alwani Abdulkareem, 2016. A Coreference Resolution Approach using Morphological Features in Arabic. International Journal of Advanced Computer Science and Applications. Volume 7. Issue 10.",
                "links": null
            },
            "BIBREF4": {
                "ref_id": "b4",
                "title": "A Generic approach for Pronominal Anaphora and Zero Anaphora resolution in Arabic language",
                "authors": [
                    {
                        "first": "Zribi Chiraz Ben",
                        "middle": [],
                        "last": "Bouzida Saoussen Mathlouthi",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Othmane",
                        "suffix": ""
                    }
                ],
                "year": 2020,
                "venue": "proceeding of the 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Bouzida Saoussen Mathlouthi and Zribi Chiraz Ben Othmane. 2020. A Generic approach for Pronominal Anaphora and Zero Anaphora resolution in Arabic language. In proceeding of the 24th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems.",
                "links": null
            },
            "BIBREF5": {
                "ref_id": "b5",
                "title": "Affective computing and sentiment analysis",
                "authors": [
                    {
                        "first": "Cambria",
                        "middle": [],
                        "last": "Erik",
                        "suffix": ""
                    }
                ],
                "year": 2016,
                "venue": "IEEE Intelligent Systems",
                "volume": "31",
                "issue": "2",
                "pages": "102--107",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Cambria Erik. 2016. Affective computing and sentiment analysis. IEEE Intelligent Systems. Volume 31(2). Page (s) 102-107, 2016.",
                "links": null
            },
            "BIBREF6": {
                "ref_id": "b6",
                "title": "Voyellation automatique de l'arabe",
                "authors": [
                    {
                        "first": "Debili",
                        "middle": [],
                        "last": "Fathi",
                        "suffix": ""
                    },
                    {
                        "first": "Hadh\u00e9mi",
                        "middle": [],
                        "last": "Achour",
                        "suffix": ""
                    }
                ],
                "year": 1998,
                "venue": "Proceedings of the Workshop on Computational Approaches to Semitic Languages. Page (s)",
                "volume": "",
                "issue": "",
                "pages": "42--49",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Debili Fathi and Hadh\u00e9mi Achour. 1998. Voyellation automatique de l'arabe. In Proceedings of the Workshop on Computational Approaches to Semitic Languages. Page (s). 42-49.",
                "links": null
            },
            "BIBREF7": {
                "ref_id": "b7",
                "title": "A Syntactic based Approach to Anaphora Resolution in Arabic",
                "authors": [],
                "year": 2018,
                "venue": "proceeding of The Eighteenth Conference on Language Engineering (ESOLEC'18)",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "El-Said Nada Aya Nabil Mostafa, Saad Sameh and Al- Ansary Abou El-Magd. 2018. A Syntactic based Approach to Anaphora Resolution in Arabic. In proceeding of The Eighteenth Conference on Language Engineering (ESOLEC'18).",
                "links": null
            },
            "BIBREF8": {
                "ref_id": "b8",
                "title": "Anaphora resolution and word order across adulthood: Ageing effects on online listening comprehension. Glossa: a journal of general linguistics",
                "authors": [
                    {
                        "first": "Fotiadou",
                        "middle": [],
                        "last": "Georgia",
                        "suffix": ""
                    },
                    {
                        "first": "Ana",
                        "middle": [],
                        "last": "Mu\u00f1oz",
                        "suffix": ""
                    },
                    {
                        "first": "Tsimpli",
                        "middle": [],
                        "last": "P\u00e9rez",
                        "suffix": ""
                    },
                    {
                        "first": "Mari",
                        "middle": [],
                        "last": "Ianthi",
                        "suffix": ""
                    }
                ],
                "year": 2020,
                "venue": "",
                "volume": "5",
                "issue": "",
                "pages": "1--29",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Fotiadou Georgia, Mu\u00f1oz Ana P\u00e9rez and Tsimpli Ianthi Mari. 2020. Anaphora resolution and word order across adulthood: Ageing effects on online listening comprehension. Glossa: a journal of general linguistics. Volume 5. Issue 1. Page (s) 1-29.",
                "links": null
            },
            "BIBREF9": {
                "ref_id": "b9",
                "title": "Caract\u00e9risation Formelle des Ellipses de la Langue Arabe et Processus de Recouvrement de la Langue Arabe",
                "authors": [
                    {
                        "first": "Haddar",
                        "middle": [],
                        "last": "Kais",
                        "suffix": ""
                    }
                ],
                "year": 2000,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Haddar Kais.2000. Caract\u00e9risation Formelle des Ellipses de la Langue Arabe et Processus de Recouvrement de la Langue Arabe. PhD thesis, University of Tunis.",
                "links": null
            },
            "BIBREF10": {
                "ref_id": "b10",
                "title": "Arabic Anaphora Resolution: Corpora Annotation with Coreferential Links",
                "authors": [
                    {
                        "first": "Hammami",
                        "middle": [],
                        "last": "Souha",
                        "suffix": ""
                    },
                    {
                        "first": "Belguith",
                        "middle": [],
                        "last": "Lamia",
                        "suffix": ""
                    },
                    {
                        "first": "Ben",
                        "middle": [],
                        "last": "Hamadou Abdelmajid",
                        "suffix": ""
                    }
                ],
                "year": 2009,
                "venue": "The International Arab Journal of Information Technology",
                "volume": "6",
                "issue": "5",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Hammami Souha, Belguith Lamia, and Ben Hamadou Abdelmajid. 2009. Arabic Anaphora Resolution: Corpora Annotation with Coreferential Links. The International Arab Journal of Information Technology. Volume 6, No. 5.",
                "links": null
            },
            "BIBREF11": {
                "ref_id": "b11",
                "title": "Anaphora Resolution for Arabic Machine Translation: A Case Study of Nafs",
                "authors": [
                    {
                        "first": "Hamouda",
                        "middle": [],
                        "last": "Wafya",
                        "suffix": ""
                    }
                ],
                "year": 2014,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Hamouda Wafya. 2014. Anaphora Resolution for Arabic Machine Translation: A Case Study of Nafs. Ph.D. dissertation, University of Newcastle Upon Tyne.",
                "links": null
            },
            "BIBREF12": {
                "ref_id": "b12",
                "title": "Time frame as a determinant of accessibility of anaphoric demonstratives in Classical Arabic",
                "authors": [
                    {
                        "first": "Jarbou",
                        "middle": [],
                        "last": "Samer",
                        "suffix": ""
                    },
                    {
                        "first": "Omar",
                        "middle": [],
                        "last": "",
                        "suffix": ""
                    }
                ],
                "year": 2018,
                "venue": "Topics in Linguistics",
                "volume": "19",
                "issue": "",
                "pages": "57--71",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Jarbou Samer Omar. 2018. Time frame as a determinant of accessibility of anaphoric demonstratives in Classical Arabic. Topics in Linguistics. Volume 19. Issue 2. Page (s) 57-71.",
                "links": null
            },
            "BIBREF13": {
                "ref_id": "b13",
                "title": "Pronoun Resolution Task for Multilingual Machine Translation",
                "authors": [
                    {
                        "first": "Madhura",
                        "middle": [],
                        "last": "Phadke",
                        "suffix": ""
                    },
                    {
                        "first": "Satish",
                        "middle": [],
                        "last": "Devane",
                        "suffix": ""
                    }
                ],
                "year": 2019,
                "venue": "Proceeding of the 5th International Conference on Next Generation Computing Technologies",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Madhura Phadke, and Satish Devane. 2019. Pronoun Resolution Task for Multilingual Machine Translation. In Proceeding of the 5th International Conference on Next Generation Computing Technologies (NGCT-2019).",
                "links": null
            },
            "BIBREF14": {
                "ref_id": "b14",
                "title": "How to combine salience factors for Arabic Pronoun Anaphora Resolution",
                "authors": [],
                "year": 2017,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Mathlouthi Bouzid Saoussen, Zribi Chiraz Ben Othmane and Trabelsi F\u00e9riel Ben Fraj. 2017. How to combine salience factors for Arabic Pronoun Anaphora Resolution. In the proceeding of the 4th",
                "links": null
            },
            "BIBREF15": {
                "ref_id": "b15",
                "title": "ACS/IEEE International Conference on Computer Systems and Applications",
                "authors": [],
                "year": null,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "ACS/IEEE International Conference on Computer Systems and Applications.",
                "links": null
            },
            "BIBREF16": {
                "ref_id": "b16",
                "title": "Information Extraction Systems and Nominal Anaphora Analysis Needs",
                "authors": [
                    {
                        "first": "Matysiak",
                        "middle": [],
                        "last": "Ireneusz",
                        "suffix": ""
                    }
                ],
                "year": 2007,
                "venue": "Proceedings of the International Multiconference on Computer Science and Information Technology. Page (s)",
                "volume": "",
                "issue": "",
                "pages": "183--192",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Matysiak Ireneusz. 2007. Information Extraction Systems and Nominal Anaphora Analysis Needs. In Proceedings of the International Multiconference on Computer Science and Information Technology. Page (s) 183-192.",
                "links": null
            },
            "BIBREF17": {
                "ref_id": "b17",
                "title": "Anaphora resolution: The state of the art",
                "authors": [
                    {
                        "first": "Mitkov",
                        "middle": [],
                        "last": "Ruslan",
                        "suffix": ""
                    }
                ],
                "year": 1999,
                "venue": "Paper based on the COLING'98/ACL'98",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Mitkov Ruslan 1999. Anaphora resolution: The state of the art. In Paper based on the COLING'98/ACL'98",
                "links": null
            },
            "BIBREF19": {
                "ref_id": "b19",
                "title": "Madamira: A fast, comprehensive tool for morphological analysis and disambiguation of Arabic",
                "authors": [
                    {
                        "first": "Pasha",
                        "middle": [],
                        "last": "Arfath",
                        "suffix": ""
                    },
                    {
                        "first": "Al-Badrashiny",
                        "middle": [],
                        "last": "Mohamed",
                        "suffix": ""
                    },
                    {
                        "first": "Diab",
                        "middle": [],
                        "last": "Mona",
                        "suffix": ""
                    },
                    {
                        "first": "Eskander",
                        "middle": [],
                        "last": "El Kholy Ahmed",
                        "suffix": ""
                    },
                    {
                        "first": "Habash",
                        "middle": [],
                        "last": "Ramy",
                        "suffix": ""
                    },
                    {
                        "first": "Pooleery",
                        "middle": [],
                        "last": "Nizar",
                        "suffix": ""
                    },
                    {
                        "first": "Rambow",
                        "middle": [],
                        "last": "Manoj",
                        "suffix": ""
                    },
                    {
                        "first": "Roth",
                        "middle": [],
                        "last": "Owen",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Ryan",
                        "suffix": ""
                    }
                ],
                "year": 2014,
                "venue": "the Proceeding of LREC. Page (s)",
                "volume": "",
                "issue": "",
                "pages": "1094--1101",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Pasha Arfath , Al-Badrashiny Mohamed , Diab Mona , El Kholy Ahmed , Eskander Ramy , Habash Nizar , Pooleery Manoj , Rambow Owen , Roth Ryan. 2014. Madamira: A fast, comprehensive tool for morphological analysis and disambiguation of Arabic. In the Proceeding of LREC. Page (s) 1094- 1101.",
                "links": null
            },
            "BIBREF20": {
                "ref_id": "b20",
                "title": "Anaphora Resolution. Chapter of book",
                "authors": [
                    {
                        "first": "Mahmoud",
                        "middle": [],
                        "last": "Seddik Khadiga",
                        "suffix": ""
                    },
                    {
                        "first": "Farghaly",
                        "middle": [],
                        "last": "Ali",
                        "suffix": ""
                    }
                ],
                "year": 2014,
                "venue": "Theory and Applications of Natural Language Processing",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Seddik Khadiga Mahmoud and Farghaly Ali. 2014. Anaphora Resolution. Chapter of book, Theory and Applications of Natural Language Processing, Springer.",
                "links": null
            },
            "BIBREF21": {
                "ref_id": "b21",
                "title": "Arabic Anaphora Resolution Using Holy Qur'an Text As Corpus",
                "authors": [
                    {
                        "first": "Mahmoud",
                        "middle": [],
                        "last": "Seddik Khadiga",
                        "suffix": ""
                    },
                    {
                        "first": "Farghaly",
                        "middle": [],
                        "last": "Ali",
                        "suffix": ""
                    }
                ],
                "year": 2011,
                "venue": "proceeding of Arabic Language Technology International Conference (ALTIC)",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Seddik Khadiga Mahmoud and Farghaly.Ali. 2011. Arabic Anaphora Resolution Using Holy Qur'an Text As Corpus. In proceeding of Arabic Language Technology International Conference (ALTIC).",
                "links": null
            },
            "BIBREF22": {
                "ref_id": "b22",
                "title": "Arabic Anaphora Resolution: Corpus of the Holy Qur'an Annotated with Anaphoric Information",
                "authors": [
                    {
                        "first": "Seddik",
                        "middle": [],
                        "last": "Khadiga",
                        "suffix": ""
                    },
                    {
                        "first": "Farghaly",
                        "middle": [],
                        "last": "Ali",
                        "suffix": ""
                    },
                    {
                        "first": "Fahmy Aly",
                        "middle": [],
                        "last": "Aly",
                        "suffix": ""
                    }
                ],
                "year": 2015,
                "venue": "International Journal of Computer Applications",
                "volume": "124",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Seddik Khadiga, Farghaly Ali and Fahmy Aly Aly. 2015. Arabic Anaphora Resolution: Corpus of the Holy Qur'an Annotated with Anaphoric Information. International Journal of Computer Applications. Volume 124. Issue 15.",
                "links": null
            },
            "BIBREF23": {
                "ref_id": "b23",
                "title": "QurAna. Corpus of the Quran annotated with Pronominal Anaphora",
                "authors": [
                    {
                        "first": "Sharaf",
                        "middle": [],
                        "last": "Abdul Baquee",
                        "suffix": ""
                    },
                    {
                        "first": "Atwell",
                        "middle": [],
                        "last": "Eric",
                        "suffix": ""
                    }
                ],
                "year": 2012,
                "venue": "the Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Sharaf Abdul baquee.,and Atwell Eric. 2012. QurAna. Corpus of the Quran annotated with Pronominal Anaphora. In the Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12).",
                "links": null
            },
            "BIBREF24": {
                "ref_id": "b24",
                "title": "Anaphora and Coreference Resolution: A Review. Information Fusion",
                "authors": [
                    {
                        "first": "Sukthanker",
                        "middle": [],
                        "last": "Rhea",
                        "suffix": ""
                    },
                    {
                        "first": "Poria",
                        "middle": [],
                        "last": "Soujanya",
                        "suffix": ""
                    },
                    {
                        "first": "Cambria",
                        "middle": [],
                        "last": "Erik",
                        "suffix": ""
                    },
                    {
                        "first": "Thirunavukarasu",
                        "middle": [],
                        "last": "Ramkumar",
                        "suffix": ""
                    }
                ],
                "year": 2020,
                "venue": "",
                "volume": "59",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Sukthanker Rhea, Poria Soujanya, Cambria Erik and Thirunavukarasu Ramkumar. 2020. Anaphora and Coreference Resolution: A Review. Information Fusion. Volume 59.",
                "links": null
            },
            "BIBREF25": {
                "ref_id": "b25",
                "title": "Arabic Anaphora Resolution Using Markov Decision Process",
                "authors": [],
                "year": 2016,
                "venue": "the Proceeding 17 th International Conference on Intelligent Text Processing and Computational Linguistics",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Trabelsi F\u00e9riel Ben Fraj, Zribi Chiraz Ben Othmane and Mathlouthi Saoussen. 2016. Arabic Anaphora Resolution Using Markov Decision Process. In the Proceeding 17 th International Conference on Intelligent Text Processing and Computational Linguistics.",
                "links": null
            },
            "BIBREF26": {
                "ref_id": "b26",
                "title": "A Novel Approach Based on Reinforcement Learning for Anaphora Resolution",
                "authors": [
                    {
                        "first": "",
                        "middle": [],
                        "last": "Trabelsi F\u00e9riel Ben Fraj",
                        "suffix": ""
                    }
                ],
                "year": 2016,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Trabelsi f\u00e9riel ben fraj. 2016. A Novel Approach Based on Reinforcement Learning for Anaphora Resolution. In the proceeding of the 28th International Business Information Management conference.",
                "links": null
            },
            "BIBREF27": {
                "ref_id": "b27",
                "title": "Anaphora Resolution in Dialogue Systems for South Asian Languages",
                "authors": [
                    {
                        "first": "Vinay",
                        "middle": [],
                        "last": "Annam",
                        "suffix": ""
                    },
                    {
                        "first": "Nikhil",
                        "middle": [],
                        "last": "Koditala",
                        "suffix": ""
                    },
                    {
                        "first": "Radhika",
                        "middle": [],
                        "last": "Mamidi",
                        "suffix": ""
                    }
                ],
                "year": 2019,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {
                    "arXiv": [
                        "arXiv:1911.09994"
                    ]
                },
                "num": null,
                "urls": [],
                "raw_text": "Vinay Annam, Nikhil Koditala and Radhika Mamidi. 2019. Anaphora Resolution in Dialogue Systems for South Asian Languages. arXiv:1911.09994.",
                "links": null
            }
        },
        "ref_entries": {
            "FIGREF0": {
                "num": null,
                "type_str": "figure",
                "text": "Example of verbal anaphora.",
                "uris": null
            },
            "FIGREF1": {
                "num": null,
                "type_str": "figure",
                "text": "Example of lexical anaphora.",
                "uris": null
            },
            "FIGREF2": {
                "num": null,
                "type_str": "figure",
                "text": "Example of comparative anaphora.",
                "uris": null
            },
            "FIGREF3": {
                "num": null,
                "type_str": "figure",
                "text": "Example of disjoint personal pronoun anaphora.",
                "uris": null
            },
            "FIGREF4": {
                "num": null,
                "type_str": "figure",
                "text": "Example of pleonastic pronoun.Relative pronouns ( \u202b\u0627\u0644\u0645\u0648\u0635\u0648\u0644\u0629\u202c \u202b:)\u0627\u0623\u0644\u0633\u0645\u0627\u0621\u202c Relative pronouns in Arabic have the characteristic of being always anaphoric, in addition they have only one possible referent(Trabelsi, 2016) and refer to the immediate nominal phrase mentioned before(Bouzid et al., 2014)  which they agree in gender and number.",
                "uris": null
            },
            "FIGREF5": {
                "num": null,
                "type_str": "figure",
                "text": "Example of relative anaphora.",
                "uris": null
            },
            "FIGREF6": {
                "num": null,
                "type_str": "figure",
                "text": "Example of demonstrative anaphora.",
                "uris": null
            },
            "FIGREF7": {
                "num": null,
                "type_str": "figure",
                "text": "Example of agglutination.",
                "uris": null
            },
            "FIGREF8": {
                "num": null,
                "type_str": "figure",
                "text": "Example of ambiguity of the referent.",
                "uris": null
            },
            "FIGREF9": {
                "num": null,
                "type_str": "figure",
                "text": "Example of hidden referent.",
                "uris": null
            },
            "FIGREF10": {
                "num": null,
                "type_str": "figure",
                "text": "General architecture of building A 3 C.",
                "uris": null
            },
            "FIGREF11": {
                "num": null,
                "type_str": "figure",
                "text": "POS by MADAMIRA.",
                "uris": null
            },
            "FIGREF12": {
                "num": null,
                "type_str": "figure",
                "text": "Score similarity (example in pronominal case).",
                "uris": null
            },
            "FIGREF13": {
                "num": null,
                "type_str": "figure",
                "text": "Anaphora resolution heuristics.",
                "uris": null
            },
            "FIGREF14": {
                "num": null,
                "type_str": "figure",
                "text": "Score similarity (example in pronominal case)",
                "uris": null
            },
            "TABREF0": {
                "text": "",
                "content": "<table><tr><td>Translation: \"Students who are about</td><td/></tr><tr><td>to graduate must complete their</td><td/></tr><tr><td>administrative file, if they do not, they will not receive their certificates.\"</td><td>Referent</td></tr><tr><td>Verbal Anaphora</td><td/></tr><tr><td>Translation: \"Ibn Sina was born in</td><td/></tr><tr><td>Bukhara (in present-day Uzbekistan),</td><td/></tr><tr><td>one of the most famous writings of</td><td/></tr><tr><td>the scientist The Canon of Medicine\".</td><td>Referent</td></tr><tr><td/><td>Nada et</td></tr><tr><td/><td>al., 2018):</td></tr><tr><td>Lexical Anaphora</td><td/></tr></table>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF1": {
                "text": "",
                "content": "<table><tr><td>Translation: \"Departure of Vessels</td></tr><tr><td>transporting more than 50,000 tons</td></tr><tr><td>of agricultural nutrients (urea) and</td></tr><tr><td>various other from the industrial</td></tr><tr><td>port of AL Jubail in the Kingdom to</td></tr><tr><td>the Port Sudan in Khartoum.\"</td></tr><tr><td>Comparative Anaphora</td></tr></table>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF3": {
                "text": "Example of ambiguities due to the lack of diacritics.",
                "content": "<table/>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF4": {
                "text": ": \"I think it is in our interest to work hard\".",
                "content": "<table><tr><td>Pleonastic</td><td/><td/><td/></tr><tr><td>Pronoun</td><td/><td/><td/></tr><tr><td>Translation: \"This book is for my brother Samir.\"</td><td>Word</td><td>Word + Diacritics \u202b\u064e\u0640\u0628\u064e\u202c \u202b\u0640\u062a\u0640\u202c \u064e \u202b\u0643\u0640\u202c \u202b\u0640\u0628\u202c \u064f \u202b\u0640\u062a\u0640\u202c \u064f \u202b\u0643\u0640\u202c</td><td>Translation he wrote books</td></tr><tr><td/><td>\u202b\u0643\u0640\u0640\u062a\u0640\u0640\u0628\u202c</td><td>\u202b\u0650\u0640\u0628\u064e\u202c \u202b\u0640\u062a\u0640\u202c \u064f \u202b\u0643\u0640\u202c</td><td>Written</td></tr><tr><td/><td/><td>\u202b\u0650\u0640\u0628\u064e\u202c \u202b\u0640\u062a\u0640\u202c \u064f \u202b\u0643\u0640\u202c</td><td>was caused to write</td></tr><tr><td>Referent</td><td/><td/><td/></tr></table>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF6": {
                "text": "Words free order in Arabic sentences.",
                "content": "<table/>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF7": {
                "text": "",
                "content": "<table><tr><td/><td/><td>Translation:</td><td>\"The</td></tr><tr><td/><td/><td colspan=\"2\">student successfully</td></tr><tr><td/><td/><td colspan=\"2\">passed the exam because he is assiduous, despite his</td><td>The first Joint Personal Pronoun</td></tr><tr><td/><td/><td>difficulty\".</td><td>refer to \"Student\".</td></tr><tr><td>Translation: \"and with their books\".</td><td/><td>Agglutinated word</td><td>The second Joint Personal Pronoun refer to \"Exam\"</td></tr><tr><td>Enclitic</td><td/><td>Proclitic</td></tr><tr><td>(Their)</td><td/><td>(and with)</td></tr><tr><td>\u202b\u0647\u0645\u202c</td><td>+</td><td>\u202b\u0648\u0628\u0640\u202c</td></tr></table>",
                "html": null,
                "num": null,
                "type_str": "table"
            },
            "TABREF10": {
                "text": "The linguistic preferences and their respective Scores.",
                "content": "<table/>",
                "html": null,
                "num": null,
                "type_str": "table"
            }
        }
    }
}