File size: 66,504 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
{
    "paper_id": "P92-1016",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T08:11:45.662331Z"
    },
    "title": "UNDERSTANDING NATURAL LANGUAGE INSTRUCTIONS: THE CASE OF PURPOSE CLAUSES",
    "authors": [
        {
            "first": "Barbara",
            "middle": [],
            "last": "Di",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "University of Pennsylvania Philadelphia",
                "location": {
                    "region": "PA"
                }
            },
            "email": "dieugeni@linc.cis.upenn.edu"
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "This paper presents an analysis of purpose clauses in the context of instruction understanding. Such analysis shows that goals affect the interpretation and / or execution of actions, lends support to the proposal of using generation and enablement to model relations between actions, and sheds light on some inference processes necessary to interpret purpose clauses.",
    "pdf_parse": {
        "paper_id": "P92-1016",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "This paper presents an analysis of purpose clauses in the context of instruction understanding. Such analysis shows that goals affect the interpretation and / or execution of actions, lends support to the proposal of using generation and enablement to model relations between actions, and sheds light on some inference processes necessary to interpret purpose clauses.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [
            {
                "text": "A speake~ (S) gives instructions to a hearer CrI) in order to affect H's behavior. Researchers including (Winograd, 1972) , (Chapman, 1991) , (Vere and Bickmore, 1990) , (Cohen and Levesque, 1990) , (Alterman et al., 1991) have been and are addressing many complex facets of the problem of mapping Natural Language instructions onto an agent's behavior. However, an aspect that no one has really considered is computing the objects of the intentions H's adopts, namely, the actions to be performed. In general, researchers have equated such objects with logical forms extracted from the NL input. This is perhaps sufficient for simple positive imperatives, but more complex imperatives require that action descriptions be computed, not simply extracted, from the input instruction. To clarify my point, consider: Ex. 1 a) Place a plank between two ladders. b) Place a plank between two ladders to create a simple scaffold.",
                "cite_spans": [
                    {
                        "start": 105,
                        "end": 121,
                        "text": "(Winograd, 1972)",
                        "ref_id": null
                    },
                    {
                        "start": 124,
                        "end": 139,
                        "text": "(Chapman, 1991)",
                        "ref_id": "BIBREF3"
                    },
                    {
                        "start": 142,
                        "end": 167,
                        "text": "(Vere and Bickmore, 1990)",
                        "ref_id": "BIBREF8"
                    },
                    {
                        "start": 170,
                        "end": 196,
                        "text": "(Cohen and Levesque, 1990)",
                        "ref_id": "BIBREF3"
                    },
                    {
                        "start": 199,
                        "end": 222,
                        "text": "(Alterman et al., 1991)",
                        "ref_id": "BIBREF1"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTRODUCTION",
                "sec_num": null
            },
            {
                "text": "In both a) and b), the action to be executed is place a plank between two ladders. However, Ex. 1.a would be correctly interpreted by placing the plank anywhere between the two ladders: this shows that in b) H must be inferring the proper position for the plank from the expressed goal to create a simple scaffold. Therefore, the goal an action is meant to achieve constrains the interpretation and / or the execution of the action itself.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTRODUCTION",
                "sec_num": null
            },
            {
                "text": "The infinitival sentence in Ex. 1.b is a purpose clause, *Mailing addxess: IRCS -3401, Walnut St -Suite 40(0 -Philadelphia, PA, 19104 -USA. which, as its name says, expresses the agent's purpose in performing a certain action. The analysis of purpose clauses is relevant to the problem of understanding Natural Language instructions, because:",
                "cite_spans": [
                    {
                        "start": 124,
                        "end": 139,
                        "text": "PA, 19104 -USA.",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTRODUCTION",
                "sec_num": null
            },
            {
                "text": "1. Purpose clauses explicitly encode goals and their interpretation shows that the goals that H adopts guide his/her computation of the action(s) to perform. 2. Purpose clauses appear to express generation or enablement, supporting the proposal, made by (Allen, 1984) , (Pollack, 1986) , (Grosz and Sidner, 1990) , (Balkansld, 1990) , that these two relations are necessary m model actions.",
                "cite_spans": [
                    {
                        "start": 254,
                        "end": 267,
                        "text": "(Allen, 1984)",
                        "ref_id": "BIBREF0"
                    },
                    {
                        "start": 270,
                        "end": 285,
                        "text": "(Pollack, 1986)",
                        "ref_id": null
                    },
                    {
                        "start": 288,
                        "end": 312,
                        "text": "(Grosz and Sidner, 1990)",
                        "ref_id": null
                    },
                    {
                        "start": 315,
                        "end": 332,
                        "text": "(Balkansld, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTRODUCTION",
                "sec_num": null
            },
            {
                "text": "After a general description of purpose clauses, I will concentrate on the relations between actions that they express, and on the inference processes that their interpretation requires. I see these inferences as instantiations of general accommodation processes necessary to interpret instructions, where the term accommodation is borrowed from (Lewis, 1979). I will conclude by describing the algorithm that implements the proposed inference processes.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTRODUCTION",
                "sec_num": null
            },
            {
                "text": "I am not the first one to analyze purpose clauses: however, they have received attention almost exclusively from a syntactic point of view -see for example (Jones, 1985) , (l-Iegarty, 1990) . Notice that I am not using the term purpose clause in the technical way it has been used in syntax, where it refers to infinitival to clauses adjoined to NPs. In contrast, the infinitival clauses I have concentrated on are adjoined to a matrix clause, and are termed rational clauses in syntax; in fact all the data I will discuss in this paper belong to a particular subclass of such clauses, subject-gap rational clauses.",
                "cite_spans": [
                    {
                        "start": 156,
                        "end": 169,
                        "text": "(Jones, 1985)",
                        "ref_id": "BIBREF7"
                    },
                    {
                        "start": 172,
                        "end": 189,
                        "text": "(l-Iegarty, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "As far as I know, very little attention has been paid to purpose clauses in the semantics literature: in (1990), Jackendoff briefly analyzes expressions of purpose, goal, or rationale, normally encoded as an infinitival, in order to-phrase, or for-phrase. He represents them by means of a subordinating function FOR, which has the adjunct clause as an argument; in turn, FOR plus its argument is a restrictive modifier of the main clause. However, Jackendoff's semantic decomposition doesn't go beyond the construction of the logical form of a sentence, and he doesn't pursue the issue of what the relation between the actions described in the matrix and adjunct really is.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "The only other work that mentions purpose clauses in a computational setting is (Balkanski, 1991) . However, she doesn't present any linguistic analysis of the data; as I will show, such analysis raises many interesting issues, such as t:",
                "cite_spans": [
                    {
                        "start": 80,
                        "end": 97,
                        "text": "(Balkanski, 1991)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "\u2022 It is fairly clear that S uses purpose clauses to explain to H the goal/~ to whose achievement the execution of contributes. However, an important point that had been overlooked so far is that the goal/~ also constrains the interpretation of ~, as I observed with respect to Ex. 1.b. Another example in point is: Ex. 2 Cut the square in half to create two triangles.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "The action to be performed is cutting the square in half. However, such action description is underspecified, in that there is an infinite number of ways of cutting a square in half: the goal create two triangles restricts the choice to cutting the square along one of the two diagonals.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "\u2022 Purpose clauses relate action descriptions at different levels of abstraction, such as a physical action and an abstract process, or two physical actions, but at different levels of granularity:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "Ex. 3 Heat on stove to simmer.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "\u2022 As far as what is described in purpose clauses, I have been implying that both matrix and purpose clauses describe an action, c~ and/~ respectively. There are rare cases -in fact, I found only one -in which one of the two clauses describes a state ~r:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "Ex. 4 To be successfully covered, a wood wall must be flat and smooth.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "I haven't found any instances in which both matrix and purpose clauses describe a state. Intuitively, this makes sense because S uses a purpose clause to inform H of the purpose of a given action 2",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "\u2022 In most cases, the goal /~ describes a change in the world. However, in some cases 1. The change is not in the world, but in H's knowledge. By executing o~, H can change the state of his knowledge with respect to a certain proposition or to the value of a certain entity.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "1I collected one hundred and one consecutive instances of purpose clauses from a how-to-do book on installing wall coverings, and from two craft magazines.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "~There are clearly other ways of describing that a state is the goal of a certain action, for example by means of so~such that, but I won't deal with such data here. Ex. 5 You may want to hang a coordinating border around the room at the top of the walls. To determine the amount of border, measure the width (in feet) of all walls to be covered and divide by three. Since borders are sold by the yard, this will give you the number of yards needed.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "Many of such examples involve verbs such as check, make sure etc.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "followed by a thatcomplement describing a state ~b. The use of such verbs has the pragmatic effect that not only does H check whether ~b holds, but, if ~b doesn't hold, s/he will also do something so that ff comes to hold.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "Ex. 6 To attach the wires to the new switch, use the paper clip to move the spring type clip aside and slip the wire into place. Tug gently on each wire to make sure it's secure.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "PURPOSE CLAUSES",
                "sec_num": null
            },
            {
                "text": "should not change, namely, that a given event should be prevented from happening:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The purpose clause may inform H that the world",
                "sec_num": "2."
            },
            {
                "text": "Ex. 7 Tape raw edges of fabric to prevent threads from raveling as you work.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The purpose clause may inform H that the world",
                "sec_num": "2."
            },
            {
                "text": "\u2022 From a discourse processing point of view, interpreting a purpose clause may affect the discourse model, in particular by introducing new referents. This happens when the effect of oL is to create a new object, and/~ identifies it. Verbs frequently used in this context are create, make, form etc.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The purpose clause may inform H that the world",
                "sec_num": "2."
            },
            {
                "text": "Ex. 8 Join the short ends of the hat band to form a circle.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The purpose clause may inform H that the world",
                "sec_num": "2."
            },
            {
                "text": "Similarly, in Ex. 2 the discourse referents for the triangles created by cutting the square in half, and in Ex. 5 the referent for amount of border are introduced.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "The purpose clause may inform H that the world",
                "sec_num": "2."
            },
            {
                "text": "So far, I have mentioned that oe contributes to achieving the goal/~. The notion of contribution can be made more specific by examining naturally occurring purpose clauses. In the majority of cases, they express generation, and in the rest enablement. Also (Grosz and Sidner, 1990) use contribute as a relation between actions, and they define it as a place holder for any relation ... that can hold between actions when one can be said to contribute (for example, by generating or enabling) to the performance of the other. However, they don't justify this in terms of naturally occurring data. Balkanski (1991) does mention that purpose clauses express generation or enablement, but she doesn't provide evidence to support this claim. GENERATION Generation is a relation between actions that has been extensively studied, first in philosophy (Goldman, 1970) and then in discourse analysis (Allen, 1984) , (Pollack, 1986) , (Grosz and Sidner, 1990) , (Balkanski, 1990) . According to Goldman, intuitively generation is the relation between actions conveyed by the preposition by in English -turning on the light by flipping the switch.",
                "cite_spans": [
                    {
                        "start": 844,
                        "end": 859,
                        "text": "(Goldman, 1970)",
                        "ref_id": "BIBREF6"
                    },
                    {
                        "start": 891,
                        "end": 904,
                        "text": "(Allen, 1984)",
                        "ref_id": "BIBREF0"
                    },
                    {
                        "start": 907,
                        "end": 922,
                        "text": "(Pollack, 1986)",
                        "ref_id": null
                    },
                    {
                        "start": 925,
                        "end": 949,
                        "text": "(Grosz and Sidner, 1990)",
                        "ref_id": null
                    },
                    {
                        "start": 952,
                        "end": 969,
                        "text": "(Balkanski, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "RELATIONS BETWEEN ACTIONS",
                "sec_num": null
            },
            {
                "text": "More formally, we can say that an action a conditionally generates another action/~ iff 3:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "RELATIONS BETWEEN ACTIONS",
                "sec_num": null
            },
            {
                "text": "1. a and/~ are simultaneous; 2. a is not part of doing/~ (as in the case of playing a C note as part of playing a C triad on a piano);",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "RELATIONS BETWEEN ACTIONS",
                "sec_num": null
            },
            {
                "text": "3. when a occurs, a set of conditions C hold, such that the joint occurrence of a and C imply the occurrence of/L In the case of the generation relation between flipping the switch and turning on the light, C will include that the wire, the switch and the bulb are working.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "RELATIONS BETWEEN ACTIONS",
                "sec_num": null
            },
            {
                "text": "Although generation doesn't hold between o~ and fl if is part of a sequence of actions ,4 to do/~, generation may hold between the whole sequence ,4 and/~. Generation is a pervasive relation between action descriptions in naturally occurring data. However, it appears from my corpus that by clauses are used less frequently than purpose clauses to express generation 4: about 95% of my 101 purpose clauses express generation, while in the same corpus there are only 27 by clauses. It does look like generation in instructional text is mainly expressed by means of purpose clauses. They may express either a direct generation relation between and/~, or an indirect generation relation between and/~, where by indirect generation I mean that ~ belongs to a sequence of actions ,4 which generates 8.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "RELATIONS BETWEEN ACTIONS",
                "sec_num": null
            },
            {
                "text": "Following first Pollack (1986) and then Balkanski (1990) , enablement holds between two actions ~ and /~ if and only if an occurrence of ot brings about a set of conditions that are necessary (but not necessarily sufficien 0 for the subsequent performance of 8. Only about 5% of my examples express enablement:",
                "cite_spans": [
                    {
                        "start": 16,
                        "end": 30,
                        "text": "Pollack (1986)",
                        "ref_id": null
                    },
                    {
                        "start": 40,
                        "end": 56,
                        "text": "Balkanski (1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "ENABLEMENT",
                "sec_num": null
            },
            {
                "text": "Ex. 9 Unscrew the protective plate to expose the box.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "ENABLEMENT",
                "sec_num": null
            },
            {
                "text": "Unscrew the protective plate enables taking the plate off which generates exposing the box.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "ENABLEMENT",
                "sec_num": null
            },
            {
                "text": "That purpose clauses do express generation and enablement is a welcome finding: these two relations have been proposed as necessary to model actions (Allen, 1984) , (Pollack, 1986) , (Grosz and Sidner, 1990) , (Balkanski, 1990) , but this proposal has not been justiffed by offering an extensive analysis of whether and how these relations are expressed in NL.",
                "cite_spans": [
                    {
                        "start": 149,
                        "end": 162,
                        "text": "(Allen, 1984)",
                        "ref_id": "BIBREF0"
                    },
                    {
                        "start": 165,
                        "end": 180,
                        "text": "(Pollack, 1986)",
                        "ref_id": null
                    },
                    {
                        "start": 183,
                        "end": 207,
                        "text": "(Grosz and Sidner, 1990)",
                        "ref_id": null
                    },
                    {
                        "start": 210,
                        "end": 227,
                        "text": "(Balkanski, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "3Goldman distinguishes among four kinds of generation relations: subsequent work has been mainly influenced by conditional generation.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "4Generation can also be expressed with a simple free adjunct; however, this use of free adjuncts is not very common -see 0hrebber and Di Eugenio, 1990) .",
                "cite_spans": [
                    {
                        "start": 137,
                        "end": 151,
                        "text": "Eugenio, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "A further motivation for using generation and enablement in modeling actions is that they allow us to draw conclusions about action execution as well -a particularly useful consequence given that my work is taking place in the framework of the Animation from Natural Language -AnimNL project (Badler eta/., 1990; in which the input instructions do have to be executed, namely, animated.",
                "cite_spans": [
                    {
                        "start": 292,
                        "end": 312,
                        "text": "(Badler eta/., 1990;",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "As has already been observed by other researchers, ff generates /~, two actions are described, but only a, the generator, needs to be performed. In Ex. 2, there is no creating action per se that has to be executed: the physical action to be performed is cutting, constrained by the goal as explained above.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "In contrast to generation, if a enables/~, after executing or, fl still needs to be executed: a has to temporally precede/~, in the sense that a has to begin, but not necessarily end, before/3. In Ex. 10, ho/d has to continue for the whole duration offal/:",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "Ex. 10 Hold the cup under the spigot to fill it with coffee.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "Notice that, in the same way that the generatee affects the execution of the generator, so the enabled action affects the execution of the enabling action. Consider the difference in the interpretation of to in go to the mirror, depending upon whether the action to be enabled is seeing oneself or carrying the mirror somewhere else.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "GENERATION AND ENABLEMENT IN MODELING ACTIONS",
                "sec_num": null
            },
            {
                "text": "So far, I have been talking about the purpose clause constraining the interpretation of the matrix clause. I will now provide some details on how such constraints are computed. The inferences that I have identified so far as necessary to interpret purpose clauses can be described as 1. Computing a more specific action description. 2. Computing assumptions that have to hold for a certain relation between actions to hold.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INFERENCE PROCESSES",
                "sec_num": null
            },
            {
                "text": "Computing more specific action descriptions.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INFERENCE PROCESSES",
                "sec_num": null
            },
            {
                "text": "In Ex. 2 -Cut the square in half to create two triangles -it is necessary to find a more specific action al which will achieve the goal specified by the purpose clause, as shown in Fig. 1 . For Ex. 2 we have fl = create two triangles, o~ = cut the square in half, ~1 = cut the square in half along the diagonal. The reader will notice that the inputs to accommodation are linguistic expressions, while its outputs are predicate -argument structures: I have used the latter in Fig. 1 to indicate that accommodation infers relations between action types. However, as I will show later, the representation I adopt is not based on predicate -argument structures. Also notice that I am using Greek symbols for both linguistic expressions and action types: the context should be sufficient to disambiguate which one is meant. Presumably, H doesn't have a particular plan that deals with getting an urn of coffee. S/he will have a generic plan about get x, which s/he will adapt to the instructions S gives him 5. In particular, H has to find the connection between go into the other room and get the urn of coffee. This connection requires reasoning about the effects of go with respect to the plan get x; notice that the (most direc0 connection between these two actions requires the assumption that the referent of the urn of coffee is in the other room. Schematically, one could represent this kind of inference as in Fig. 2 -/~ is the goal, ~ the instruction to accommodate, Ak the actions belonging to the plan to achieve t, C the necessary assumptions. It could happen that these two kinds of inference need to be combined: however, no example I have found so far requires it.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 181,
                        "end": 187,
                        "text": "Fig. 1",
                        "ref_id": null
                    },
                    {
                        "start": 476,
                        "end": 482,
                        "text": "Fig. 1",
                        "ref_id": null
                    },
                    {
                        "start": 1415,
                        "end": 1421,
                        "text": "Fig. 2",
                        "ref_id": "FIGREF0"
                    }
                ],
                "eq_spans": [],
                "section": "INFERENCE PROCESSES",
                "sec_num": null
            },
            {
                "text": "In this section, I will describe the algorithm that im-5Actually H may have more than one single plan for get x,. in which case go into the other room may in fact help to select the plan the instructor has in mind. plements the two kinds of accommodation described in the previous section. Before doing that, I will make some remarks on the action representation I adopt and on the structure of the intentions -the plan graph -that my algorithm contributes to building. Action representation. To represent action types, I use an hybrid system (Brachman et al., 1983) , whose primitives are taken from Jackendoff's Conceptual Structures (1990) ; relations between action types are represented in another module of the system, the action library.",
                "cite_spans": [
                    {
                        "start": 543,
                        "end": 566,
                        "text": "(Brachman et al., 1983)",
                        "ref_id": "BIBREF2"
                    },
                    {
                        "start": 625,
                        "end": 642,
                        "text": "Structures (1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "I'd like to spend a few words justifying the choice of an hybrid system: this choice is neither casual, nor determined by the characteristics of the AnimNL project.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "Generally, in systems that deal with NL instructions, action types are represented as predicate -argument structures; the crucial assumption is then made that the logical form of an input instruction will exactly match one of these definitions. However, there is an infinite number of NL descriptions that correspond to a basic predicate -argument structure: just think of all the possible modifiers that can be added to a basic sentence containing only a verb and its arguments. Therefore it is necessary to have a flexible knowledge representation system that can help us understand the relation between the input description and the stored one. I claim that hybrid KR systems provide such flexibility, given their virtual lattice structure and the classification algorithm operating on the lattice: in the last section of this paper I will provide an example supporting my claim.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "Space doesn't allow me to deal with the reason why Conceptual Structures are relevant, namely, that they are useful to compute assumptions. For further details, the interested reader is referred to (Di Di Eugenic) and White, 1992) .",
                "cite_spans": [
                    {
                        "start": 202,
                        "end": 213,
                        "text": "Di Eugenic)",
                        "ref_id": null
                    },
                    {
                        "start": 218,
                        "end": 230,
                        "text": "White, 1992)",
                        "ref_id": "BIBREF5"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "Just a reminder to the reader that hybrid systems have two components: the terminological box, or T-Box, where concepts are defined, and on which the classification algorithm works by computing subsumption relations between different concepts. The algorithm is crucial for adding new concepts to the KB: it computes the subsumption relations between the new concept and all the other concepts in the lattice, so that it can \"Position\" the new concept in the right place in the lattice. The other component of an hybrid system is the assertional box, or A-box, where assertions are stored, and which is equipped with a theorem-prover.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "In my case, the T-Box contains knowledge about action types, while assertions about individual actionsinstances of the types -are contained in the A-Box: such individuals correspond to the action descriptions contained in the input instructions 6",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "The action library contains simple plans relating actions; simple plans are either generation or enablement relations between pairs: the first member of the pair is either a single action or a sequence of action, and the second member is an action. In case the first member of the pair is an individual action, I will talk about direct generation or enablement. For the moment, generation and enablement are represented in a way very similar to (Balkanski, 1990) .",
                "cite_spans": [
                    {
                        "start": 445,
                        "end": 462,
                        "text": "(Balkanski, 1990)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "The plan graph represents the structure of the intentions derived from the input instructions. It is composed of nodes that contain descriptions of actions, and arcs that denote relations between them. A node contains the Conceptual Structures representation of an action, augmented with the consequent state achieved after the execution of that action. The arcs represent, among others: temporal relations; generation; enablement.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "The plan graph is built by an interpretation algorithm that works by keeping track of active nodes, which for the moment include the goal currently in focus and the nodes just added to the graph; it is manipulated by various inference processes, such as plan expansion, and plan recognition.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "My algorithm is described in Fig. 3 7. Clearly the inferences I describe are possible only because I rely ~Notice that these individuals are simply instances of generic concepts, and not necessarily action tokens, namely, nothing is asserted with regard to their happening in the world.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 29,
                        "end": 35,
                        "text": "Fig. 3",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "rAs I mentioned earlier in the paper, the Greek symbols on the other AnimNL modules for 1) parsing the input and providing a logical form expressed in terms of Conceptual Structures primitives; 2) managing the discourse model, solving anaphora, performing temporal inferences etc (Webber eta/., 1991) .",
                "cite_spans": [
                    {
                        "start": 280,
                        "end": 300,
                        "text": "(Webber eta/., 1991)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "INTERPRETING Do a to do I~",
                "sec_num": null
            },
            {
                "text": "I will conclude by showing how step 4a in Fig. 3 takes advantage of the classification algorithm with which hybrid systems are equipped. Consider the T-Box, or better said, the portion of T-Box shown in Fig. 4 s. Given Ex. 2 -Cut the square in half to create two triangles -as input, the individual action description cut (the) square in half will be asserted in the A-Box and recognized as an instance of ~ -the shaded concept cut (a) square in half -which is a descendant of cut and an abstraction of o: -cut (a) square in half along the diagonal, as shown in Fig. 5 9. Notice that this does not imply that the concept cut (a) square in half is known beforehand: the classification process is able to recognize it as a virtual concept and to find the right place for it in the lattice 10. Given that a is ancestor of o J, and that oJ generates/~ -create two triangles, the fact that the action to be performed is actually o~ and not oL can be inferred. This implements step 4(a)ii.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 42,
                        "end": 48,
                        "text": "Fig. 3",
                        "ref_id": null
                    },
                    {
                        "start": 203,
                        "end": 212,
                        "text": "Fig. 4 s.",
                        "ref_id": null
                    },
                    {
                        "start": 562,
                        "end": 568,
                        "text": "Fig. 5",
                        "ref_id": "FIGREF2"
                    }
                ],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "The classification process can also help to deal with cases in which ~ is in conflict with to -step 4(a)iv. If were cut (a) square along a perpendicular axis, a conflict with o~ -cut (a) square in half along the diagonal -would be recognized. Given the T-Box in fig. 4 , the classification process would result in o~ being a sister to w: my algorithm would try to unify them, but this would not be possible, because the role fillers of location on and w cannot be unified, being along(perpendicularaxis) and along(diagonal) respectively. I haven't addressed the issue yet of which strategies to adopt in case such a conflict is detected.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 262,
                        "end": 268,
                        "text": "fig. 4",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "Another point left for future work is what to do when step 2 yields more than one simple plan. The knowledge representation system I am using is BACK (Peltason et al., 1989) ; the algorithm is being implemented in QUINTUS PROLOG. refer both to input descriptions and to action types.",
                "cite_spans": [
                    {
                        "start": 150,
                        "end": 173,
                        "text": "(Peltason et al., 1989)",
                        "ref_id": "BIBREF7"
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "SThe reader may find that the representation in Fig. 4 is not very perspicuous, as it mixes linguistic expressions, such as along(diagonal), with conceptual knowledge about entities. Actually, roles and concepts are expressed in terms of Conceptual Structures primitives, which provide a uniform way of representing knowledge apparently belonging to different types. However, a T-Box expressed in terms of Conceptual Structures becomes very complex, so in Fig. 4 I adopted a more readable representation.",
                "cite_spans": [],
                "ref_spans": [
                    {
                        "start": 48,
                        "end": 54,
                        "text": "Fig. 4",
                        "ref_id": null
                    },
                    {
                        "start": 456,
                        "end": 462,
                        "text": "Fig. 4",
                        "ref_id": null
                    }
                ],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "9The agent role does not appear on cut square in half in the A-Box for the sake of readability.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "1\u00b0In fact, such concept is not really added to the lattice. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "AN EXAMPLE OF THE ALGORITHM",
                "sec_num": null
            },
            {
                "text": "I have shown that the analysis of purpose clauses lends support to the proposal of using generation and enablement to model actions, and that the interpretation of purpose clauses originates specific inferences: I have illustrated two of them, that can be seen as examples of accommodation processes (Lewis, 1979) , and that show how the bearer's inference processes are directed by the goal(s) s/he is adopting.",
                "cite_spans": [
                    {
                        "start": 300,
                        "end": 313,
                        "text": "(Lewis, 1979)",
                        "ref_id": null
                    }
                ],
                "ref_spans": [],
                "eq_spans": [],
                "section": "CONCLUSIONS",
                "sec_num": null
            },
            {
                "text": "Future work includes fully developing the action representation formalism, and the algorithm, especially the part regarding computing assumptions.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "CONCLUSIONS",
                "sec_num": null
            }
        ],
        "back_matter": [
            {
                "text": "For financial support I acknowledge DARPA grant no. N0014-90-J-1863 and ARt grant no. DAALO3-89-C0031PR1. Thanks to Bonnie Webber for support, insights and countless discussions, and to all the members of the AnimNL group, in particular to Mike White. Finally, thanks to the Dipartimento di Informatica -Universita' di Torino -Italy for making their computing environment available to me, and in particular thanks to Felice Cardone, Luca Console, Leonardo Lesmo, and Vincenzo Lombardo, who helped me through a last minute computer crash.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "ACKNOWLEDGEMENTS",
                "sec_num": null
            },
            {
                "text": "Input: the Conceptual Structures logical forms for ~ and t, the current plan graph, and the list of active nodes.1. Add to A-Box individuals corresponding to the two logical forms. Set flag ACCOM if they don't exactly match known concepts.2. Retrieve from the action library the simple plan(s) associated with /5 -generation relations in which /5 is the generate., enablement relations in which/5 is the enablee.3. If ACCOM is not set (a) If there is a direct generation or enablement relation between ~ and/5, augment plan graph with the structure derived from it, after calling compute-assumptions. (b) If there is no such direct relation, recursively look for possible connections between e and the components 7i of sequences that either generate or enable/5. Augment plan graph, after calling c omput e-a s s umpt i on s.4. If ACCOM is set, (a) If there is ~a such that oJ directly generates or enables/5, check whether i. w is an ancestor of c~: take c~ as the intended action.ii. ~o is a descendant of c~: take o~ as the intended action. iii. If w and e are not ancestors of each other, but they can be unified -all the information they provide is compatible, as in the case of cut square in half along diagonal and cut square carefully -then their unification w U c~ is the action to be executed. iv. If o: and ~ are not ancestors of each other, and provide conflicting information -such as cut square along diagonal and cut square along perpendicular axis -then signal failure. (b) If there is no such w, look for possible connections between ~ and the components 7i of sequences that either generate or enable/5, as in step 3b. Given that ~ is not known to the system, apply the inferences described in 4a to c~ and 7/. ",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "annex",
                "sec_num": null
            }
        ],
        "bib_entries": {
            "BIBREF0": {
                "ref_id": "b0",
                "title": "Towards a general theory of action and time",
                "authors": [
                    {
                        "first": "Allen ; James",
                        "middle": [],
                        "last": "Allen",
                        "suffix": ""
                    }
                ],
                "year": 1984,
                "venue": "Artificial Intelligence",
                "volume": "23",
                "issue": "",
                "pages": "123--154",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Allen, 1984) James Allen. Towards a general theory of action and time. Artificial Intelligence, 23:123- 154, 1984.",
                "links": null
            },
            "BIBREF1": {
                "ref_id": "b1",
                "title": "Interaction, Comprehension, and Instruction Usage",
                "authors": [
                    {
                        "first": "/",
                        "middle": [],
                        "last": "Alterman",
                        "suffix": ""
                    },
                    {
                        "first": "Roland",
                        "middle": [],
                        "last": "Richard Alterman",
                        "suffix": ""
                    },
                    {
                        "first": "Tamitha",
                        "middle": [],
                        "last": "Zito-Wolf",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Carpenter",
                        "suffix": ""
                    }
                ],
                "year": 1991,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Alterman eta/., 1991) Richard Alterman, Roland Zito- Wolf, and Tamitha Carpenter. Interaction, Com- prehension, and Instruction Usage. Technical Re- port CS-91-161, Dept. of Computer Science, Cen- ter for Complex Systems, Brandeis University, 1991.",
                "links": null
            },
            "BIBREF2": {
                "ref_id": "b2",
                "title": "Balkanski, 1991) Cecile Balkanski. Logical form of complex sentences in task-oriented dialogues",
                "authors": [
                    {
                        "first": "(",
                        "middle": [],
                        "last": "Badler",
                        "suffix": ""
                    }
                ],
                "year": 1983,
                "venue": "Proceedings of the 29th Annual Meeting of the ACL, Student Session",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "(Badler et al., 1990) Norman Badler, Bonnie Webber, Jeff Esakov, and Jugal Kalita. Animation from in- slzuctions. In Badler, Barsky, and Zeltzer, editors, Making them Move, MIT Press, 1990. (Balkanski, 1990) Cecile Balkanski. Modelling act-type relations in collaborative activity. Technical Re- port TR-23-90, Center for Research in Computing Technology, Harvard University, 1990. (Balkanski, 1991) Cecile Balkanski. Logical form of complex sentences in task-oriented dialogues. In Proceedings of the 29th Annual Meeting of the ACL, Student Session, 1991. (Brachman et al., 1983) R. Brachman, R.Fikes, and H. Levesque. KRYPTON: A Functional Approach to Knowledge Representation. Technical Re- port FLAIR 16, Fairchild Laboratories for Artificial Intelligence, Palo Alto, California, 1983.",
                "links": null
            },
            "BIBREF3": {
                "ref_id": "b3",
                "title": "Rational Interaction as the Basis for Communication",
                "authors": [
                    {
                        "first": "David",
                        "middle": [],
                        "last": "Chapman",
                        "suffix": ""
                    },
                    {
                        "first": "Philip",
                        "middle": [],
                        "last": "Chapman",
                        "suffix": ""
                    },
                    {
                        "first": "Hector",
                        "middle": [],
                        "last": "Cohen",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Levesque",
                        "suffix": ""
                    }
                ],
                "year": 1990,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Chapman, 1991) David Chapman. Vision, Instruction andAction. Cambridge: MIT Press, 1991. (Cohen and Levesque, 1990) Philip Cohen and Hector Levesque. Rational Interaction as the Basis for Communication. In J. Morgan, P. Cohen, and M. Pollack, editors, Intentions in Communication, MIT Press, 1990.",
                "links": null
            },
            "BIBREF4": {
                "ref_id": "b4",
                "title": "Goals andActions in Natural Language Instructions",
                "authors": [
                    {
                        "first": "Di",
                        "middle": [],
                        "last": "Eugenio",
                        "suffix": ""
                    },
                    {
                        "first": "; Barbara",
                        "middle": [],
                        "last": "Dieugenio",
                        "suffix": ""
                    }
                ],
                "year": 1992,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Di Eugenio, 1992) Barbara DiEugenio. Goals andAc- tions in Natural Language Instructions. Technical Report MS-CIS-92-07, University of Pennsylvania, 1992.",
                "links": null
            },
            "BIBREF5": {
                "ref_id": "b5",
                "title": "On the Interpretation of Natural Language Instructions",
                "authors": [
                    {
                        "first": "Di",
                        "middle": [],
                        "last": "Eugenio",
                        "suffix": ""
                    },
                    {
                        "first": "; Barbara Di",
                        "middle": [],
                        "last": "White",
                        "suffix": ""
                    },
                    {
                        "first": "Michael",
                        "middle": [],
                        "last": "Eugenio",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "White",
                        "suffix": ""
                    }
                ],
                "year": 1992,
                "venue": "",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Di Eugenio and White, 1992) Barbara Di Eugenio and Michael White. On the Interpretation of Natural Language Instructions. 1992. COLING 92.",
                "links": null
            },
            "BIBREF6": {
                "ref_id": "b6",
                "title": "Hegarty, 1990)Michael Hegarty. Secondary Predication and Null Operators in English. 1990. Manuscript. (Jackendoff, 1990) Ray Jackendoff. Semantic Structures",
                "authors": [
                    {
                        "first": "Alvin",
                        "middle": [],
                        "last": "Goldman",
                        "suffix": ""
                    }
                ],
                "year": 1970,
                "venue": "Intentions in Communication",
                "volume": "",
                "issue": "",
                "pages": "",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "(Goldman, 1970) Alvin Goldman. A Theory of Hwnan Action. Princeton University Press, 1970. (Grosz and Sidner, 1990) Barbara Grosz and Candace Sidner. Plans for Discourse. In J. Morgan, P. Co- hen, and M. Pollack, editors, Intentions in Commu- nication, MIT Press, 1990. (Hegarty, 1990)Michael Hegarty. Secondary Predi- cation and Null Operators in English. 1990. Manuscript. (Jackendoff, 1990) Ray Jackendoff. Semantic Struc- tures. Current Studies in Linguistics Series, The MIT Press, 1990.",
                "links": null
            },
            "BIBREF7": {
                "ref_id": "b7",
                "title": "1986) Martha Pollack. Inferring domain plans in question-answering",
                "authors": [
                    {
                        "first": "; Charles",
                        "middle": [],
                        "last": "Jones",
                        "suffix": ""
                    },
                    {
                        "first": ";",
                        "middle": [
                            "C"
                        ],
                        "last": "Jones",
                        "suffix": ""
                    },
                    {
                        "first": "A",
                        "middle": [],
                        "last": "Peltason",
                        "suffix": ""
                    },
                    {
                        "first": "C",
                        "middle": [],
                        "last": "Schmiedel",
                        "suffix": ""
                    },
                    {
                        "first": "J",
                        "middle": [],
                        "last": "Kindermann",
                        "suffix": ""
                    },
                    {
                        "first": "",
                        "middle": [],
                        "last": "Quantz",
                        "suffix": ""
                    }
                ],
                "year": 1979,
                "venue": "Chicago Linguistic Society",
                "volume": "21",
                "issue": "",
                "pages": "339--359",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "Jones, 1985) Charles Jones. Agent, patient, and con- trol into purpose clauses. In Chicago Linguistic Society, 21, 1985. (Lewis, 1979) David Lewis. Scorekeeping in a lan- guage game. Journal of Philosophical Language, 8:339-359, 1979. (Peltason et al., 1989) C. Peltason, A. Schmiedel, C. Kindermann, and J. Quantz. The BACK System Revisited. Technical Report KIT 75, Technische Universitaet Berlin, 1989. (Pollack, 1986) Martha Pollack. Inferring domain plans in question-answering. PhD thesis, University of Pennsylvania, 1986.",
                "links": null
            },
            "BIBREF8": {
                "ref_id": "b8",
                "title": "Webber and Di Eugenio, 1990) Bonnie Webber and Barbara Di Eugenio. Free Adjuncts in Natural Language Instructions",
                "authors": [
                    {
                        "first": "Bickmore ; Steven",
                        "middle": [],
                        "last": "Vere",
                        "suffix": ""
                    },
                    {
                        "first": "Timothy",
                        "middle": [],
                        "last": "Bickmore",
                        "suffix": ""
                    },
                    {
                        "first": ";",
                        "middle": [],
                        "last": "Webber",
                        "suffix": ""
                    }
                ],
                "year": 1972,
                "venue": "Proceedings Thirteenth International Conference on Computational Linguistics, COLING 90",
                "volume": "6",
                "issue": "",
                "pages": "395--400",
                "other_ids": {},
                "num": null,
                "urls": [],
                "raw_text": "and Bickmore, 1990) Steven Vere and Timothy Bickmore. A basic agent. Computational Intel- ligence, 6:41--60, 1990. (Webber and Di Eugenio, 1990) Bonnie Webber and Barbara Di Eugenio. Free Adjuncts in Natural Lan- guage Instructions. In Proceedings Thirteenth In- ternational Conference on Computational Linguis- tics, COLING 90, pages 395--400, 1990. (Webber et al., 1991) Bonnie Webber, Norman Badler, Barbara Di Eugenio, Libby Levison, and Michael white. Instructing Animated Agents. In Proc. US- Japan Workshop on Integrated Systems in Multi- Media Environments. Las Cruces, NM, 1991. (Winograd, 1972) Terry Winograd. Understanding Nat- ural Language. Academic Press, 1972.",
                "links": null
            }
        },
        "ref_entries": {
            "FIGREF0": {
                "uris": null,
                "text": "Computing assumptions. Let's consider: Schematic depiction of the second kind of accommodation Ex. 11 Go into the other room to get the urn of coffee.",
                "type_str": "figure",
                "num": null
            },
            "FIGREF2": {
                "uris": null,
                "text": "Dealing with less specific action descriptions",
                "type_str": "figure",
                "num": null
            }
        }
    }
}