forked from ad-freiburg/aqqu
-
Notifications
You must be signed in to change notification settings - Fork 0
/
test1.log
944 lines (884 loc) · 49.1 KB
/
test1.log
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
Query: what movie did danny devito win an award for in 1981
Entity: (u'Award (Chivalric Title)', 1.0, 214152, False)
Entity: (u'Danny DeVito', 0.999885402143, 52351, True)
Entity: (u'1981 Irish hunger strike', 0.677418808325, 583, False)
Entity: (u'FIL Award', 0.588235220761, 89, False)
Entity: (u'The Axemen', 0.193548949844, 1531, False)
Entity: (u'Twitter', 0.164705313107, 19446405, False)
Entity: (u'Pacem in Terris Award', 0.152941805869, 180, False)
Entity: (u'United States presidential election, 1980', 0.129032241831, 26, False)
Entity: (u'Film', 0.498307458078, 3444452, False)
Entity: (u'1981', 0, 0, True)
TargetType: Other
Root Node: Danny DeVito
Candidate Graph: QueryCandidate [pattern:ERMRERT
Entity [name:Danny DeVito, Danny DeVito: tokens:danny,devito prob:1.000 score:52351 perfect_match:True]
->Relation [name:award.award_winner.awards_won, award.award_winner.awards_won -> award.award_honor.year:
RelationName: win=winner,win=win,award=award,award=award,award=award,award=award,award=award
RelationNameSynonym: win=winner:0.55,win=win:1.00,award=award:1.00,award=award:1.00,award=award:1.00,award=honor:0.51]
Variable [index:0]
->Relation [name:award.award_honor.year, award.award_winner.awards_won -> award.award_honor.year:
RelationName: win=winner,win=win,award=award,award=award,award=award,award=award,award=award
RelationNameSynonym: win=winner:0.55,win=win:1.00,award=award:1.00,award=award:1.00,award=award:1.00,award=honor:0.51]
->Relation [name:award.award_honor.award, award.award_honor.award:
RelationName: award=award,award=award,award=award
DerivationMatch: award=award,award=award,award=honor,award=award
RelationNameSynonym: award=award:1.00,award=honor:0.51,award=award:1.00]
Entity [name:1981, 1981: tokens:1981 prob:0.000 score:0 perfect_match:True]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRERT
[Danny DeVito (m.0q9kd)] -> [award.award_winner.awards_won] -> [?0]
[?0] -> [award.award_honor.year] -> [1981]
[?0] -> [award.award_honor.award] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.0q9kd fb:award.award_winner.awards_won ?0 .
?0 fb:award.award_honor.year "1981"^^xsd:datetime .
?0 fb:award.award_honor.award ?1 .
FILTER (?1 != fb:m.0q9kd && ?1 != "1981"^^xsd:datetime)
} LIMIT 300
Result: Primetime Emmy Award for Outstanding Supporting Actor - Comedy Series (m.09qv3c) Primetime Emmy Award for Outstanding Supporting Actor in a Comedy, Variety or Music Series (m.0t4r672)
Query: when did japan end as a musical group
Entity: (u'Musical ensemble', 0.983225293265, 120561, False)
Entity: (u'Send in the Clowns', 0.693379984885, 895, False)
Entity: (u'Asa', 0.17427230227, 37629, True)
Entity: (u'Japan', 0.922832946225, 31422360, True)
Entity: (u'Group', 0.176437573469, 846, True)
Entity: (u'Social group', 0.138610333259, 11792, False)
Entity: (u'Group', 0.133716825004, 749, True)
TargetType: Date
Root Node: Japan
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:Japan, Japan: tokens:japan prob:0.923 score:31422360 perfect_match:True]
->Relation [name:military.military_combatant.military_conflicts, military.military_combatant.military_conflicts -> military.military_combatant_group.combatants:
RelationName: group=group
DerivationMatch: group=group
RelationContext: end:0.0010,group:0.0012
RelationNameSynonym: group=group:1.00]
Variable [index:0]
->Relation [name:military.military_combatant_group.combatants, military.military_combatant.military_conflicts -> military.military_combatant_group.combatants:
RelationName: group=group
DerivationMatch: group=group
RelationContext: end:0.0010,group:0.0012
RelationNameSynonym: group=group:1.00]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[Japan (m.03_3d)] -> [military.military_combatant.military_conflicts] -> [?0]
[?0] -> [military.military_combatant_group.combatants] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.03_3d fb:military.military_combatant.military_conflicts ?0 .
?0 fb:military.military_combatant_group.combatants ?1 .
FILTER (?1 != fb:m.03_3d)
} LIMIT 300
Result:
Query: what sort of weave is used to make tweed
Entity: (u'GNU/Linux', 1.0, 7995206, False)
Entity: (u'Newfoundland and Labrador', 0.999980274967, 101392, False)
Entity: (u'Clarence Thomas', 0.513434075445, 155203, False)
Entity: (u'Fenway Park', 0.378319068515, 185205, False)
Entity: (u'Medicare', 0.108091373211, 2941905, False)
Entity: (u'Tweed', 0.511330286787, 10762, True)
Entity: (u'Artificial hair integrations', 0.476172290178, 9107, False)
Entity: (u'Weaving', 0.321245010874, 44182, False)
Entity: (u'sort', 0.257736795752, 247, True)
Entity: (u'Sort, Lleida', 0.249271273773, 51, False)
Entity: (u'Strategic Offensive Reductions Treaty', 0.24425471268, 3612, False)
Entity: (u'River Tweed', 0.168975605687, 7474, False)
Entity: (u'Weave', 0.104803172017, 370, True)
TargetType: Other
Root Node: Newfoundland and Labrador
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:Newfoundland and Labrador, Newfoundland and Labrador: tokens:to,make prob:1.000 score:101392 perfect_match:False]
->Relation [name:symbols.coat_of_arms_bearer.coat_of_arms_used, symbols.coat_of_arms_bearer.coat_of_arms_used -> symbols.armorial_grant.coat_of_arms:
RelationName: use=use
DerivationMatch: use=use
RelationNameSynonym: use=use:1.00,tweed=coat:0.44,tweed=coat:0.44,tweed=coat:0.44]
Variable [index:0]
->Relation [name:symbols.armorial_grant.coat_of_arms, symbols.coat_of_arms_bearer.coat_of_arms_used -> symbols.armorial_grant.coat_of_arms:
RelationName: use=use
DerivationMatch: use=use
RelationNameSynonym: use=use:1.00,tweed=coat:0.44,tweed=coat:0.44,tweed=coat:0.44]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[Newfoundland and Labrador (m.05j49)] -> [symbols.coat_of_arms_bearer.coat_of_arms_used] -> [?0]
[?0] -> [symbols.armorial_grant.coat_of_arms] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.05j49 fb:symbols.coat_of_arms_bearer.coat_of_arms_used ?0 .
?0 fb:symbols.armorial_grant.coat_of_arms ?1 .
FILTER (?1 != fb:m.05j49)
} LIMIT 300
Result: Coat of arms of St. John's, Newfoundland and Labrador (m.0958jz)
Query: what bicycle models does raleigh manufacture
Entity: (u'Bicycle Models', 0.166666666667, 0, True)
Entity: (u'Bicycle Models', 0.166666666667, 0, True)
Entity: (u'Bicycle Models', 0.166666666667, 0, True)
Entity: (u'Bicycle Models', 0.166666666667, 0, True)
Entity: (u'Bicycle models', 0.166666666667, 0, True)
Entity: (u'Bicycle models', 0.166666666667, 0, True)
Entity: (u'Bicycle', 0.955090129129, 55244, True)
Entity: (u'Raleigh', 0.770311942976, 2008038, True)
Entity: (u'Model', 0.173636206762, 78754, False)
Entity: (u'Scientific modelling', 0.115049636351, 3188, False)
TargetType: Other
Root Node: Bicycle
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Bicycle, Bicycle: tokens:bicycle prob:0.955 score:55244 perfect_match:True]
->Relation [name:base.engineeringdraft.manufactured_component_category.meronyms, base.engineeringdraft.manufactured_component_category.meronyms:
RelationName: manufacture=manufacture
DerivationMatch: manufacture=manufacture
RelationNameSynonym: manufacture=manufacture:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Bicycle (m.0199g)] -> [base.engineeringdraft.manufactured_component_category.meronyms] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.0199g fb:base.engineeringdraft.manufactured_component_category.meronyms ?0 .
FILTER (?0 != fb:m.0199g)
} LIMIT 300
Result: Bicycle handlebar (m.02rqv26) Bicycle frame (m.01bqgn) Bicycle wheel (m.01bqk0) Crankset (m.01ms7j) Bicycle saddle (m.0g7v8f)
Query: how many writing systems are used in japanese
Entity: (u'Writing system', 0.911144873965, 2543, False)
Entity: (u'Wakame', 0.853329924581, 5563, False)
Entity: (u'Japanese general election, 1928', 0.461111064259, 0, False)
Entity: (u'Newfoundland and Labrador', 0.142221654097, 101392, False)
Entity: (u'Soramimi', 0.122222269074, 29, False)
Entity: (u'System', 0.58453182609, 83083, False)
TargetType: Other
Root Node: Wakame
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Wakame, Wakame: tokens:used,in prob:0.853 score:5563 perfect_match:False]
->Relation [name:base.schemastaging.food_extra.broader, base.schemastaging.food_extra.broader:
RelationContext: many:0.0008]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Wakame (m.040tm1)] -> [base.schemastaging.food_extra.broader] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.040tm1 fb:base.schemastaging.food_extra.broader ?0 .
FILTER (?0 != fb:m.040tm1)
} LIMIT 30000}
Result: 1
Query: what characters were on the cover of batman #1
Entity: (u'On the Cover', 0.742656151724, 47, True)
Entity: (u'On the Cover (TV Program)', 0.199568583871, 9, True)
Entity: (u'He Hit Me (Composition)', 1.0, 128, False)
Entity: (u'Twilight (Young Adult Book) #147', 0.418281104676, 2190, False)
Entity: (u'The Luv Show', 0.227066917834, 18, False)
Entity: (u'Lagopus', 0.210770954847, 272, False)
Entity: (u'The Cover', 0.197189452785, 25, True)
Entity: (u'Soviet Union', 0.164664808474, 5858281, False)
Entity: (u'Happy Nation', 0.164664808474, 38, False)
Entity: (u'David Horowitz', 0.144905183608, 65415, False)
Entity: (u'Cover version', 0.620217133283, 72764, False)
Entity: (u'Batman', 0.608938484599, 398670, True)
Entity: (u'Characters', 0.305673921723, 437, True)
TargetType: Other
Root Node: Batman
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Batman, Batman: tokens:batman prob:0.609 score:398670 perfect_match:True]
->Relation [name:comic_books.comic_book_character.cover_appearances, comic_books.comic_book_character.cover_appearances:
RelationName: character=character,cover=cover
DerivationMatch: character=character,cover=cover
RelationContext: character:0.0413
RelationNameSynonym: character=comic:0.45,character=character:1.00,cover=cover:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Batman (m.01d5g)] -> [comic_books.comic_book_character.cover_appearances] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.01d5g fb:comic_books.comic_book_character.cover_appearances ?0 .
FILTER (?0 != fb:m.01d5g)
} LIMIT 300
Result: Batman #477 (m.03dfh34) Identity Crisis #1 (m.04cp09x) Identity Crisis #6 (m.04cp0f0) Detective Comics #33 (m.030rk_k) Batman #1 (m.02wkbg7) Batwing #7 (m.0j3rxq1) Batman #568 (m.03bw1dh) Batman #68 (m.03bwqlv) Detective Comics #734 (m.03bw1p5) Shadow of the Bat #1 (m.02wm2wd) Detective Comics #27 (m.02wk9x1) Detective Comics #38 (m.02wlp16) Batman #436 (m.02wlpqt) Detective Comics #779 (m.02wlytc) World's Finest Comics #3 (m.02wlzzk) Batman #567 (m.030rjwt) Detective Comics #411 (m.030rk6x) Detective Comics #741 (m.03bvjsf) Detective Comics #580 (m.03bx0cp) Superman/Batman #47 (m.042_zcz) Batman #611 (m.09vvtf1) Batman #612 (m.09vvwdt) Secret Origins, Vol. 1 (m.030rl69) Detective Comics #140 (m.02wlzl_) Batman #426 (m.02wkc7r) Batman #427 (m.02wkc9c)
Query: how many episodes of taylor made piano were there
Entity: (u'TaylorMade-Adidas', 0.605763224569, 58054, False)
Entity: (u'Piano', 0.833676442114, 147843, True)
Entity: (u'Episode', 0.176139928418, 22364, False)
Entity: (u'Episodes', 0.157919044247, 4070, True)
Entity: (u'Pianos', 0.140255452171, 21389, False)
TargetType: Other
Query: who is the present newscaster on cbs evening news
Entity: (u'CBS Evening News', 0.99231284123, 237659, True)
Entity: (u'The Evening News (Newspaper) #2', 0.322500187702, 129, True)
Entity: (u'The Present', 0.317390777508, 284, True)
Entity: (u'Edinburgh Evening News', 0.214999545135, 6912, False)
Entity: (u'The Present', 0.203398315164, 182, True)
Entity: (u'The Present (Rock Album)', 0.182164425119, 163, True)
Entity: (u'CBS', 0.856024728164, 1667770, True)
Entity: (u'News Presenter', 0.849008927996, 0, False)
Entity: (u'Evening (m/04mx32)', 0.511346892319, 36337, True)
Entity: (u'News', 0.492882295248, 131990, True)
Entity: (u'Evening (Romance Film)', 0.243171504344, 991, True)
Entity: (u'NEWS', 0.184980476678, 672, True)
Entity: (u'Evening Magazine', 0.165656777078, 1602, False)
TargetType: person, organization, employer, character
Root Node: CBS Evening News
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:CBS Evening News, CBS Evening News: tokens:cbs,evening,news prob:0.992 score:237659 perfect_match:True]
->Relation [name:tv.tv_program.program_creator, tv.tv_program.program_creator:
RelationContext: present:0.0017]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[CBS Evening News (m.01bndp)] -> [tv.tv_program.program_creator] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.01bndp fb:tv.tv_program.program_creator ?0 .
FILTER (?0 != fb:m.01bndp)
} LIMIT 300
Result: Don Hewitt (m.078q1l) CBS News (m.01_8w2)
Query: did the big bang exhibit at the science museum cost money
Entity: (u'Science Museum', 0.999929373543, 28316, True)
Entity: (u'Big Bang', 0.392090468579, 296322, True)
Entity: (u'The Big Bang', 0.173080424431, 0, True)
Entity: (u'Conservation status', 1.0, 766, False)
Entity: (u'Big Bang', 0.600751269585, 296322, True)
Entity: (u'Malaysia', 0.527271766275, 4351832, False)
Entity: (u'Cardcaptor Sakura', 0.472726779795, 46890, False)
Entity: (u'Medical cannabis', 0.460306007727, 17293, False)
Entity: (u'Big Bang (K-pop Artist)', 0.282017893058, 139106, True)
Entity: (u'Brining', 0.223576462003, 3325, False)
Entity: (u'Emotion', 0.197274003311, 23284, False)
Entity: (u'Science museum', 0.164249954413, 7702, True)
Entity: (u'Musical acoustics', 0.118364401987, 1291, False)
Entity: (u'Money (Quotation Subject)', 0.750863000671, 70037, True)
Entity: (u'Collection (Organisation sector)', 0.239241545864, 14554, False)
Entity: (u'Art exhibition', 0.230697347509, 51269, False)
Entity: (u'Exhibit', 0.205064253453, 93, True)
Entity: (u'Bang!', 0.201390239198, 1630, True)
Entity: (u'Ernesto Neto', 0.119620772932, 3879, False)
Entity: (u'Bang! (Book) #37', 0.103042613185, 834, True)
Entity: (u'Exhibit', 0.102531877232, 0, True)
Entity: (u"Vincent van Gogh's display at Les XX, 1890", 0.102531877232, 0, False)
TargetType: Other
Root Node: Science Museum
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:Science Museum, Science Museum: tokens:the,science,museum prob:1.000 score:28316 perfect_match:True]
->Relation [name:exhibitions.exhibition_venue.exhibitions_at_this_venue, exhibitions.exhibition_venue.exhibitions_at_this_venue:
RelationName: exhibit=exhibition,exhibit=exhibition,exhibit=exhibition
RelationNameSynonym: exhibit=exhibition:0.71,exhibit=exhibition:0.71]
Variable [index:0]
->Relation [name:exhibitions.exhibition_run.admission_fee, exhibitions.exhibition_run.admission_fee:
RelationName: exhibit=exhibition,exhibit=exhibition
RelationNameSynonym: exhibit=exhibition:0.71,cost=fee:0.50]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[Science Museum (m.013yrz)] -> [exhibitions.exhibition_venue.exhibitions_at_this_venue] -> [?0]
[?0] -> [exhibitions.exhibition_run.admission_fee] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.013yrz fb:exhibitions.exhibition_venue.exhibitions_at_this_venue ?0 .
?0 fb:exhibitions.exhibition_run.admission_fee ?1 .
FILTER (?1 != fb:m.013yrz)
} LIMIT 300
Result: 0 1
Query: in what season of stargate sg-1 is the episode show and tell
Entity: (u'Show and Tell (Musical Recording) #34', 0.189136131061, 126, True)
Entity: (u'Show and tell', 0.133596156067, 89, True)
Entity: (u'Show and tell', 0.102073467557, 68, True)
Entity: (u'Stargate SG-1', 0.971065355264, 144974, True)
Entity: (u'Burr\u2013Hamilton duel', 0.618213820768, 271, False)
Entity: (u'The Strike (TV Episode) #1', 0.202219249023, 0, False)
Entity: (u'Stargate (Fictional Universe)', 0.390924840692, 21596, True)
Entity: (u'Episode', 0.292628485896, 22364, True)
Entity: (u'Season', 0.283846106731, 10457, True)
Entity: (u'Season', 0.277508146975, 29811, True)
Entity: (u'Stargate (Science Fiction Film)', 0.174839456559, 2195, True)
Entity: (u'Stargate', 0.167295734986, 22793, True)
Entity: (u'Stargate (Fictional Object)', 0.103086553801, 9803, True)
TargetType: Other
Root Node: Stargate SG-1
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Stargate SG-1, Stargate SG-1: tokens:stargate,sg-1 prob:0.971 score:144974 perfect_match:True]
->Relation [name:tv.tv_program.episodes, tv.tv_program.episodes:
RelationName: episode=episode
RelationContext: season:0.0199,episode:0.1075,show:0.0041,tell:0.0040
RelationNameSynonym: episode=episode:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Stargate SG-1 (m.09kn9)] -> [tv.tv_program.episodes] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.09kn9 fb:tv.tv_program.episodes ?0 .
FILTER (?0 != fb:m.09kn9)
} LIMIT 300
Result: Counterstrike (m.0cf24w) Within the Serpent's Grasp (1) (m.0hpgj1r) Thor's Hammer (m.0647nf) Desperate Measures (m.09sl0d) Evolution (2) (m.06yfkb9) Heroes (m.07m60n) Beachhead (m.07mcsq) Babylon (m.07mctr) New Order (m.07m5_l) Fragile Balance (m.07mf2m) Prometheus (m.07mf7h) Thor's Chariot (m.079rzk) Abyss (m.07p75k) Space Race (m.07md_w) Maternal Instinct (m.08msmh) Ethon (m.09yk86) Seth (m.0644vf) Prototype (m.07mcvf) Shadow Play (m.07mfgr) Foothold (m.0697mp) A Matter of Time (m.08mp85) Jolinar's Memories (m.08mr3b) The Devil You Know (m.08msdj) Cold Lazarus (m.06476g) Redemption (2) (m.06yfk8b) The Fourth Horseman (2) (m.06yfkg9) Redemption (m.07m61b) Full Alert (m.07mckh) Disclosure (m.07mf9x) 48 Hours (m.09sl25) Crusade (m.0b0fs6) Camelot (m.0b0fsx) Flesh and Blood (m.0br51c) Covenant (m.07mcmk) Sight Unseen (m.07mfby) Proving Ground (m.09jyyl) The Sentinel (m.09rryk) Between Two Fires (m.09sk_0) Red Sky (m.09skq2) Demons (m.08mqtz) The Warrior (m.09gqyq) The Quest (1) (m.06yfkhg) Prisoners (m.079r9n) Children of the Gods (m.041178) Threads (m.07mcjf) Out of Mind (m.07mcwt) Hathor (m.0647yv) Family (m.07b_14) Into the Fire (m.07mcy5) Spirits (m.03910v) The Enemy Within (m.0608sd) 1969 (m.060vv6) Emancipation (m.064713) The Broca Divide (m.06472v) The First Commandment (m.06474_) The Nox (m.0647d0) Brief Candle (m.0647hj) The Torment of Tantalus (m.0647r6) Bloodlines (m.0647s_) Fire and Water (m.0647vd) Singularity (m.064822) Cor-ai (m.064833) Enigma (m.06485j) Solitudes (m.06yfk23) Tin Man (m.06yfk2f) There But For the Grace of God (m.06yfk2r) Politics (1) (m.06yfk31) The Tok'ra (1) (m.06yfk3_) The Tok'ra (2) (m.06yfk49) Avalon (1) (m.07m5y3) The Serpent's Lair (m.07ysb8) Need (m.07ysn2) Touchstone (m.08mp4w) One False Step (m.08mpkz) Show and Tell (m.08mpny) 200 (m.0cb0_f) Moebius (2) (m.06yfkf2) Lockdown (m.07mcny) Birthright (m.07mdz3) Origin (m.07mcpz) 2001 (m.09sk_q) Off the Grid (m.0b0fp1) Unnatural Selection (m.07mf7v) Ripple Effect (m.08mlrc) Memento Mori (m.0cf25x) The Pegasus Project (m.0bqvhm) Full Circle (m.07mf4b) In the Line of Duty (m.079qw1) Fallout (m.07mdy2) Memento (m.07mfdp) Resurrection (m.07mdwq) Chain Reaction (m.092g5k) Frozen (m.07p76l) Nemesis (m.08msr_) Small Victories (m.09rb33) Tangent (m.09bc08) Point of No Return (m.09ryq7) The Shroud (m.0dmc6w) Line In The Sand (m.0dzp2m) Icon (m.07mcpm) Pretense (m.08mshc) Affinity (m.07mcn7) Reckoning (2) (m.06yfkdd) Gemini (m.07mcl5) The Changeling (m.07mfcm) The Tomb (m.09skxy) Lost City (m.06zf2x) Zero Hour (m.07mcp8) Stronghold (m.09yk9l) Ex Deus Machina (m.07ht9j) Bane (m.08mp0x) Heroes, Part 2 (m.06yfkby) Fail Safe (m.09r6px) Death Knell (m.07mdxd) Sci Fi Inside: Stargate SG-1 200 (m.0j86wp5) Scorched Earth (m.09kcnk) Insiders (m.0cf22q) Uninvited (m.0cf23v) Cure (m.07mffc) The Fourth Horseman (1) (m.06yfkf_) Forsaken (m.07mfc8) Inauguration (m.07mdw0) Point of View (m.08mqkm) The Fifth Man (m.09sknc) The Quest (2) (m.06yfkhs) Holiday (m.08mpfm) The Serpent's Venom (m.09ryv1) Allegiance (m.07mfg1) The First Ones (m.08qv9k) The Curse (m.09rysp) Shades of Grey (m.06c533) Beast of Burden (m.06hvw_) Watergate (m.06hw4_) Lost City (2) (m.06yfkcf) Avenger 2.0 (m.07mdzt) Revisions (m.07mf1y) Homecoming (m.07mf39) Fallen (m.07mf3n) Revelations (m.07nxtd) Fair Game (m.07q1m7) The Gamekeeper (m.07yslp) Learning Curve (m.08mq9k) Deadman Switch (m.08mqqh) Crystal Skull (m.08msqz) Enemies (m.09l2f_) Menace (m.09rrk4) Last Stand (2) (m.09s97h) Summit (1) (m.09s9j9) Ascension (m.09skl_) The Other Guys (m.0h3_chv) Continuum (m.0j86wry) Secrets (m.08mn_j) Window of Opportunity (m.08cz71) Nightwalkers (m.07p75x) Divide and Conquer (m.09k7qr) Upgrades (m.09rb6l) Crossroads (m.09rb89) Threshold (m.09rz91) Moebius (m.07m5cw) Wormhole X-Treme! (m.040sz8) Prophecy (m.07mff0) A Hundred Days (m.08msks) The Fifth Race (m.064pjz) Message In a Bottle (m.07bzrd) Serpent's Song (m.07mc_0) Smoke & Mirrors (m.07mf8w) Legacy (m.07q1lx) Citizen Joe (m.07mck4) Descent (m.07p76y) Talion (m.0g9lkq) Collateral Damage (m.08mlqm) Unending (m.025w7_5) Evolution (1) (m.06yfk9_) Avalon (2) (m.06yfkfg) Avatar (m.07mcnl) The Ties That Bind (m.07mcqn) Paradise Lost (m.07mfb7) Prodigy (m.07syyd) The Scourge (m.0b0fqg) Arthur's Mantle (m.0b0frh) Bounty (m.0djyr6) The Road Not Taken (m.0g0bg6) Family Ties (m.0gxbd7) 2010 (m.06fjz1) Absolute Power (m.0418qm) The Light (m.06fprj) The Other Side (m.09rb45) Bad Guys (m.0g2zpz) Stargate SG-1: True Science (m.0j86wmt) Urgo (m.08mskf) The Powers That Be (m.07mcq_) Company of Thieves (m.0cf278) It's Good to Be King (m.05tsmw) Prometheus Unbound (m.07lqlp) Endgame (m.07mclj) Yesterday, Today and Tomorrow (m.0fyb58) Morpheus (m.0cf21b) Chimera (m.07mdxr) Grace (m.07mdyf) Entity (m.09l1tt) Forever in a Day (m.068zj1) Rules of Engagement (m.08mqwd) Past and Present (m.08mqxs) Dominion (m.025w7z4) Meridian (m.09l1rc) New Ground (m.08msl3) Exodus (m.09l25_) Metamorphosis (m.07mf9k) Orpheus (m.07mf28) Enemy Mine (m.07mf0k) Lifeboat (m.07mf17) Children of the Gods (2) (m.0j86wx1) Reckoning (m.07m568) Beneath the Surface (m.09kcpy) Rite of Passage (m.09skt0) From Stargate To Atlantis - A Sci-Fi Lowdown (m.0j86wk1) Behind The Stargate - Secrets Revealed (m.0j86wlf) Double Jeopardy (m.09h2vc) Evolution (m.07m60_) Sacrifices (m.07mclw) Stargate: The Movie (m.0j86whp) The Ark of Truth (m.0j86wqk) Behind The Mythology of Stargate SG-1 (m.0j86wt9) New Order (2) (m.0j86xpn)
Query: how many beers come a can
Entity: (u'Acan', 0.659340934401, 20, True)
Entity: (u'comEA (Gene) #2', 0.5, 0, True)
Entity: (u'comEA (Gene) #1', 0.5, 0, True)
Entity: (u'Aggrecan', 0.164834983295, 382, False)
Entity: (u'Beer (Beverage type)', 0.820150180697, 62289, False)
TargetType: Other
Root Node: Acan
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Acan, Acan: tokens:a,can prob:0.659 score:20 perfect_match:True]
->Relation [name:religion.deity.deity_of, religion.deity.deity_of:
RelationContext: come:0.0010]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Acan (m.02p0xwc)] -> [religion.deity.deity_of] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.02p0xwc fb:religion.deity.deity_of ?0 .
FILTER (?0 != fb:m.02p0xwc)
} LIMIT 30000}
Result: 2
Query: what are the christian holidays
Entity: (u'Liturgical year', 1.0, 30330, False)
Entity: (u'The Christian (Book) #3', 0.443820224719, 79, True)
Entity: (u'The Christian', 0.191011235955, 463, True)
Entity: (u'The Christian', 0.191011235955, 34, True)
Entity: (u'The Christian (Musical Recording) #4', 0.101123595506, 18, True)
Entity: (u'Holiday', 0.458137425129, 581658, False)
Entity: (u'Jewish holiday', 0.197398835787, 32889, False)
Entity: (u'Buddhist holidays', 0.156667734196, 49, False)
TargetType: Other
Query: what are the texts of taoism
Entity: (u'The Texts of Taoism', 1.0, 35, True)
Entity: (u'Texts of Taoism', 0.333333333333, 0, True)
Entity: (u'Texts of Taoism (Volume 2)', 0.333333333333, 0, True)
Entity: (u'Texts of Taoism (Volume 1)', 0.333333333333, 0, True)
Entity: (u'Taoism', 0.982920151219, 399341, True)
Entity: (u'Buddhist texts', 0.400543403998, 11737, False)
Entity: (u'Hindu texts', 0.200380405858, 3294, False)
TargetType: Other
Root Node: The Texts of Taoism
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:The Texts of Taoism, The Texts of Taoism: tokens:the,texts,of,taoism prob:1.000 score:35 perfect_match:True]
->Relation [name:book.book.genre, book.book.genre:
]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[The Texts of Taoism (m.04wb9ps)] -> [book.book.genre] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.04wb9ps fb:book.book.genre ?0 .
FILTER (?0 != fb:m.04wb9ps)
} LIMIT 300
Result: Philosophy (m.037mh8)
Query: in 1982 who were the primetieme emmy award for comedy series nominees
Entity: (u'Award (Chivalric Title)', 1.0, 214152, False)
Entity: (u'Emmy Award', 0.961690893815, 651786, True)
Entity: (u'Television comedy', 0.738231871669, 7963, False)
Entity: (u'1982 FIFA World Cup', 0.71009907012, 2361, False)
Entity: (u'1982 Hama massacre', 0.170949617853, 1527, False)
Entity: (u'1982 Lebanon War', 0.118349788037, 6412, False)
Entity: (u'Resident Evil: Degeneration', 0.410762587684, 6609, False)
Entity: (u'80th Academy Awards', 0.138570825224, 5229, False)
Entity: (u'1982', 0, 0, True)
TargetType: Other
Root Node: 80th Academy Awards
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:80th Academy Awards, 80th Academy Awards: tokens:nominees prob:0.139 score:5229 perfect_match:False]
->Relation [name:award.award_ceremony.awards_presented, award.award_ceremony.awards_presented:
RelationName: award=award,award=award,award=award
RelationNameSynonym: award=award:1.00,award=award:1.00]
Variable [index:0]
->Relation [name:award.award_honor.honored_for, award.award_honor.honored_for:
RelationName: award=award,award=award
DerivationMatch: award=award,award=award,award=honor,award=honor
RelationNameSynonym: award=award:1.00,award=honor:0.51,award=honor:0.51]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[80th Academy Awards (m.02pgky2)] -> [award.award_ceremony.awards_presented] -> [?0]
[?0] -> [award.award_honor.honored_for] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.02pgky2 fb:award.award_ceremony.awards_presented ?0 .
?0 fb:award.award_honor.honored_for ?1 .
FILTER (?1 != fb:m.02pgky2)
} LIMIT 300
Result: The Golden Compass (m.04w7rn) Juno (m.02rv_dz) Michael Clayton (m.0fh694) There Will Be Blood (m.08zrbl) The Counterfeiters (m.03cgqbr) La Vie en Rose (m.02q6gfp) Falling Slowly (m.03nsp04) Ratatouille (m.03x7hd) Sweeney Todd: The Demon Barber of Fleet Street (m.0ds11z) The Bourne Ultimatum (m.061681) Peter and the Wolf (m.02vpt_d) Elizabeth: The Golden Age (m.03_gz8) No Country for Old Men (m.0b6tzs) Atonement (m.0ctb4g) Le Mozart des pickpockets (m.03qhs4f) Freeheld (m.03qhrvg) Taxi to the Dark Side (m.02qz5kl)
Query: what year was the album decade released
Entity: (u'The Album', 0.242627058026, 531, True)
Entity: (u'Album (m/02lx2r)', 0.924086966045, 118924, True)
Entity: (u'Year', 0.708396384259, 1064748, True)
Entity: (u'Decade (Unit of frequency)', 0.566263388268, 15554, True)
Entity: (u'Year', 0.244091331527, 366879, True)
Entity: (u'Fin de si\xe8cle', 0.146565609253, 923, False)
Entity: (u'Decade (Rock Album)', 0.128339579923, 48, True)
TargetType: Date
Root Node: The Album
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:The Album, The Album: tokens:the,album prob:0.243 score:531 perfect_match:True]
->Relation [name:music.album.release_date, music.album.release_date:
RelationName: release=release
DerivationMatch: release=release
RelationContext: release:0.1666,decade:0.0001,year:0.0006
RelationNameSynonym: release=release:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[The Album (m.01hnjdn)] -> [music.album.release_date] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.01hnjdn fb:music.album.release_date ?0 .
FILTER (?0 != fb:m.01hnjdn)
} LIMIT 300
Result: 1977-12-12
Query: how many countries are in south america
Entity: (u'In South America (Gramophone record Musical Release)', 0.366459568149, 0, True)
Entity: (u'In South America (Musical Album)', 0.366459568149, 0, True)
Entity: (u'South America', 0.959975493807, 3896540, True)
Entity: (u'United Nations Framework Convention on Climate Change', 0.217686725545, 327658, False)
Entity: (u'Blasphemy law', 0.200680504161, 3058, False)
Entity: (u"International Women's Day", 0.159864154474, 1136796, False)
Entity: (u'Country (Quotation Subject)', 0.840984198953, 97485, False)
TargetType: Other
Root Node: In South America (Musical Album)
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:In South America (Musical Album), In South America (Musical Album): tokens:in,south,america prob:0.366 score:0 perfect_match:True]
->Relation [name:music.album.release_type, music.album.release_type:
RelationContext: many:0.0006,country:0.0003]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[In South America (Musical Album) (m.0q8f6wp)] -> [music.album.release_type] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.0q8f6wp fb:music.album.release_type ?0 .
FILTER (?0 != fb:m.0q8f6wp)
} LIMIT 30000}
Result: 1
Query: what area did the meiji constitution govern
Entity: (u'The Meiji Constitution', 1.0, 0, True)
Entity: (u'Emperor Meiji', 1.0, 8934, False)
Entity: (u'Meiji Constitution', 0.987831850544, 2077, True)
Entity: (u'Area', 0.850698126258, 76568, True)
TargetType: Other
Root Node: Emperor Meiji
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Emperor Meiji, Emperor Meiji: tokens:the,meiji prob:1.000 score:8934 perfect_match:False]
->Relation [name:royalty.monarch.kingdom, royalty.monarch.kingdom:
RelationContext: constitution:0.0008,area:0.0005,govern:0.0005]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Emperor Meiji (m.01bsgq)] -> [royalty.monarch.kingdom] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.01bsgq fb:royalty.monarch.kingdom ?0 .
FILTER (?0 != fb:m.01bsgq)
} LIMIT 300
Result: Japan (m.03_3d)
Query: what is the collection of postcards called
Entity: (u'The Collection (Funk Album)', 0.108681689217, 251, True)
Entity: (u'Postcard', 0.801281284561, 23099, False)
Entity: (u'Collection (Organisation sector)', 0.137579251692, 14554, True)
Entity: (u'Collection', 0.11959893317, 518, True)
TargetType: Other
Root Node: Postcard
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:Postcard, Postcard: tokens:postcards prob:0.801 score:23099 perfect_match:False]
->Relation [name:interests.collection_category.collectors, interests.collection_category.collectors:
RelationName: collection=collection
RelationNameSynonym: collection=collection:1.00,collection=collector:0.53]
Variable [index:0]
->Relation [name:interests.collection.collector, interests.collection.collector:
RelationName: collection=collection
RelationNameSynonym: collection=collection:1.00,collection=collector:0.53]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[Postcard (m.0fd4f)] -> [interests.collection_category.collectors] -> [?0]
[?0] -> [interests.collection.collector] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?1 where {
fb:m.0fd4f fb:interests.collection_category.collectors ?0 .
?0 fb:interests.collection.collector ?1 .
FILTER (?1 != fb:m.0fd4f)
} LIMIT 300
Result: Chris Webber (m.02l_4s)
Query: how was pluto discovered
Entity: (u'Pluto', 0.641672151936, 513041, True)
Entity: (u'Pluto (Film character) #3', 0.123765069373, 20041, True)
TargetType: Other
Root Node: Pluto
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Pluto, Pluto: tokens:pluto prob:0.642 score:513041 perfect_match:True]
->Relation [name:astronomy.astronomical_discovery.discovery_organization, astronomy.astronomical_discovery.discovery_organization:
RelationName: discover=discovery,discover=discovery
DerivationMatch: discover=discovery,discover=discovery
RelationContext: discover:0.1337
RelationNameSynonym: discover=discovery:0.48,discover=discovery:0.48]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Pluto (m.0c3qy)] -> [astronomy.astronomical_discovery.discovery_organization] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.0c3qy fb:astronomy.astronomical_discovery.discovery_organization ?0 .
FILTER (?0 != fb:m.0c3qy)
} LIMIT 300
Result: Lowell Observatory (m.0kyyk)
Query: how many people practice buddhism
Entity: (u'Unforgettable (Composition) #374', 0.554217247046, 92, False)
Entity: (u"Medbury's-Grove Lawn Subdivisions Historic District", 0.126505920011, 0, False)
Entity: (u'Buddhism', 0.958841007958, 3064402, True)
Entity: (u'People', 0.370274503777, 228405, True)
Entity: (u'Practice', 0.339400323183, 30524, True)
Entity: (u'People (Quotation Subject)', 0.222445557315, 941, True)
Entity: (u'Praxis', 0.153781107459, 3103, False)
TargetType: Other
Root Node: Buddhism
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Buddhism, Buddhism: tokens:buddhism prob:0.959 score:3064402 perfect_match:True]
->Relation [name:religion.religion.practices, religion.religion.practices:
RelationName: practice=practice
DerivationMatch: practice=practice
RelationContext: practice:0.0104,many:0.0004
RelationNameSynonym: practice=practice:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Buddhism (m.092bf5)] -> [religion.religion.practices] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.092bf5 fb:religion.religion.practices ?0 .
FILTER (?0 != fb:m.092bf5)
} LIMIT 30000}
Result: 9
Query: how many students are there at the university of iceland
Entity: (u'University of Iceland', 1.0, 10491, True)
Entity: (u'University of Iceland', 1.0, 10491, True)
Entity: (u'Conservation status', 1.0, 766, False)
Entity: (u'Wesleyan University', 0.369864400705, 72582, False)
Entity: (u'University of Michigan', 0.167597785362, 1011854, False)
Entity: (u'University of California, Berkeley', 0.128491695109, 1709617, False)
Entity: (u'University of Oxford', 0.125910935291, 553135, False)
Entity: (u'University of Virginia', 0.111731856908, 685995, False)
Entity: (u'Uppsala University', 0.102302620021, 52141, False)
Entity: (u'Student', 0.923982877027, 95407, False)
Entity: (u'University', 0.790236592261, 1631423, True)
Entity: (u'Iceland', 0.74242798662, 1742658, True)
Entity: (u'Iceland national football team', 0.100369570192, 576, False)
TargetType: Other
Root Node: University of Iceland
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:University of Iceland, University of Iceland: tokens:the,university,of,iceland prob:1.000 score:10491 perfect_match:True]
->Relation [name:education.educational_institution.students_graduates, education.educational_institution.students_graduates:
RelationName: student=student
RelationNameSynonym: student=student:1.00,student=graduate:0.54]
Variable [index:0]
->Relation [name:education.education.student, education.education.student:
RelationName: student=student
RelationNameSynonym: student=education:0.40,student=student:1.00]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[University of Iceland (m.022hyn)] -> [education.educational_institution.students_graduates] -> [?0]
[?0] -> [education.education.student] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?1) where {
SELECT ?1 where {
fb:m.022hyn fb:education.educational_institution.students_graduates ?0 .
?0 fb:education.education.student ?1 .
FILTER (?1 != fb:m.022hyn)
} LIMIT 30000}
Result: 56
Query: how many libretti did wagner write
Entity: (u'Libretto', 0.998252922994, 14856, False)
Entity: (u'Richard Wagner', 0.720335255032, 448189, False)
TargetType: Other
Root Node: Richard Wagner
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Richard Wagner, Richard Wagner: tokens:wagner prob:0.720 score:448189 perfect_match:False]
->Relation [name:music.lyricist.lyrics_written, music.lyricist.lyrics_written:
RelationName: write=write
RelationContext: libretto:0.0007,many:0.0006,write:0.0398
RelationNameSynonym: libretto=lyricist:0.47,libretto=lyric:0.47,write=write:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Richard Wagner (m.06c44)] -> [music.lyricist.lyrics_written] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.06c44 fb:music.lyricist.lyrics_written ?0 .
FILTER (?0 != fb:m.06c44)
} LIMIT 30000}
Result: 12
Query: how many other names is ron glass known by
Entity: (u'Flash fiction', 0.439999507201, 9321, False)
Entity: (u'Goddess', 0.266666901333, 92476, False)
Entity: (u'Cochineal', 0.186666990933, 4534, False)
Entity: (u'camelCase', 0.106666600533, 47709, False)
Entity: (u'Ron Glass', 1.0, 2326, True)
Entity: (u'known by', 1.0, 0, True)
Entity: (u'Naming the American Civil War', 0.313541801419, 10198, False)
Entity: (u'Aardman Animations', 0.297297184989, 28660, False)
Entity: (u'Nir Rosen', 0.18918929401, 3744, False)
Entity: (u'Dark matter', 0.18918929401, 24942, False)
Entity: (u'Iraqi diaspora', 0.148648592495, 22, False)
Entity: (u'Glass', 0.844008317206, 223546, True)
Entity: (u'Ronald Weasley', 0.456242204414, 104582, False)
Entity: (u'Rum', 0.107941108947, 60456, False)
Entity: (u'Name', 0.100479565776, 45222, False)
TargetType: Other
Root Node: Ron Glass
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Ron Glass, Ron Glass: tokens:ron,glass prob:1.000 score:2326 perfect_match:True]
->Relation [name:people.person.profession, people.person.profession:
RelationContext: many:0.0006,name:0.0041,other:0.0004,know:0.0115]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Ron Glass (m.03h82p)] -> [people.person.profession] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.03h82p fb:people.person.profession ?0 .
FILTER (?0 != fb:m.03h82p)
} LIMIT 30000}
Result: 2
Query: what was the american past about
Entity: (u'The American Past', 0.454545454545, 5, True)
Entity: (u'The American past', 0.181818181818, 2, True)
Entity: (u'Cinema of the United States', 0.413306543581, 65777, False)
Entity: (u'The American (Novel)', 0.170842698919, 847, True)
Entity: (u'Past', 0.590100512354, 21774, True)
TargetType: Other
Root Node: The American Past
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:The American Past, The American Past: tokens:the,american,past prob:0.455 score:5 perfect_match:True]
->Relation [name:broadcast.content.artist, broadcast.content.artist:
]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[The American Past (m.05v0tbd)] -> [broadcast.content.artist] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.05v0tbd fb:broadcast.content.artist ?0 .
FILTER (?0 != fb:m.05v0tbd)
} LIMIT 300
Result: Calder Pickett (m.065m87j)
Query: who completed mozart_s requiem
Entity: (u'Requiem in D minor, K. 626 (S\xfc\xdfmayr completion): IIIf. Sequenz: "Lacrimosa"', 0.999922964332, 12980, False)
Entity: (u'Wolfgang Amadeus Mozart', 1.0, 749859, False)
Entity: (u'Requiem', 0.431997595907, 42986, True)
TargetType: person, organization, employer, character
Root Node: Requiem in D minor, K. 626 (Süßmayr completion): IIIf. Sequenz: "Lacrimosa"
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Requiem in D minor, K. 626 (Süßmayr completion): IIIf. Sequenz: "Lacrimosa", Requiem in D minor, K. 626 (Süßmayr completion): IIIf. Sequenz: "Lacrimosa": tokens:mozart_s,requiem prob:1.000 score:12980 perfect_match:False]
->Relation [name:music.composition.date_completed, music.composition.date_completed:
RelationName: complete=complete
RelationContext: complete:0.0156
RelationNameSynonym: complete=complete:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Requiem in D minor, K. 626 (Süßmayr completion): IIIf. Sequenz: "Lacrimosa" (m.02xtrr)] -> [music.composition.date_completed] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.02xtrr fb:music.composition.date_completed ?0 .
FILTER (?0 != fb:m.02xtrr)
} LIMIT 300
Result: 1791
Query: when gatorade was first developed
Entity: (u'First developed', 0.5, 0, True)
Entity: (u'First developed', 0.5, 0, True)
Entity: (u'Gatorade', 0.998550317651, 181507, True)
TargetType: Date
Root Node: Gatorade
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Gatorade, Gatorade: tokens:gatorade prob:0.999 score:181507 perfect_match:True]
->Relation [name:business.brand.products, business.brand.products:
RelationContext: develop:0.0008,first:0.0010]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Gatorade (m.01ghgx)] -> [business.brand.products] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.01ghgx fb:business.brand.products ?0 .
FILTER (?0 != fb:m.01ghgx)
} LIMIT 300
Result: Gatorade G2 (m.0rnz2d8)
Query: what are the theme areas at disneyland
Entity: (u'Theme areas', 0.5, 0, True)
Entity: (u'Theme areas', 0.5, 0, True)
Entity: (u'Disneyland', 0.937570247085, 528268, True)
Entity: (u'Area', 0.517436829902, 76568, False)
Entity: (u'L\xe9og\xe2ne', 0.115932990343, 8494, False)
TargetType: Other
Root Node: Disneyland
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Disneyland, Disneyland: tokens:disneyland prob:0.938 score:528268 perfect_match:True]
->Relation [name:location.location.area, location.location.area:
RelationName: area=area
RelationContext: theme:0.0002,area:0.0815
RelationNameSynonym: area=location:0.46,area=area:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Disneyland (m.02fzs)] -> [location.location.area] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.02fzs fb:location.location.area ?0 .
FILTER (?0 != fb:m.02fzs)
} LIMIT 300
Result: 0.647
Query: how many films has tim burton produced
Entity: (u'Bruce Lee', 1.0, 227180, False)
Entity: (u'Tim Burton', 0.994362828949, 1638763, True)
Entity: (u'Film', 0.710032297078, 3444452, False)
TargetType: Other
Root Node: Tim Burton
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Tim Burton, Tim Burton: tokens:tim,burton prob:0.994 score:1638763 perfect_match:True]
->Relation [name:film.producer.film, film.producer.film:
RelationName: produce=producer,film=film,film=film
DerivationMatch: produce=producer,film=film,film=film
RelationContext: produce:0.0371,have:0.0038,film:0.0810,many:0.0004
RelationNameSynonym: film=film:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Tim Burton (m.07rd7)] -> [film.producer.film] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?0) where {
SELECT ?0 where {
fb:m.07rd7 fb:film.producer.film ?0 .
FILTER (?0 != fb:m.07rd7)
} LIMIT 30000}
Result: 15
Query: how many politicians have served in the us navy
Entity: (u'The U.S. Navy', 0.333333333333, 0, True)
Entity: (u'The U.S. Navy', 0.333333333333, 0, True)
Entity: (u'The U.S. Navy', 0.333333333333, 0, True)
Entity: (u'Entrapment', 0.264493311955, 1724, False)
Entity: (u'Alimony', 0.15579687904, 18386, False)
Entity: (u'Treason', 0.130434649717, 46582, False)
Entity: (u'United States Navy', 0.991049786961, 1565298, False)
Entity: (u'United States of America', 0.596041510844, 149531631, False)
Entity: (u'served in', 0.5, 0, True)
Entity: (u'served in', 0.5, 0, True)
Entity: (u'German federal election, March 1933', 0.348180888537, 0, False)
Entity: (u'Th\xe9us', 0.175952614665, 4, False)
Entity: (u'Lewis Cass', 0.147169070805, 7645, False)
Entity: (u'Inthe', 0.143579278312, 0, True)
Entity: (u'Politician', 0.769146936589, 73566, False)
Entity: (u'Politics', 0.111597642535, 464041, False)
TargetType: Other
Root Node: United States Navy
Candidate Graph: QueryCandidate [pattern:ERMRT
Entity [name:United States Navy, United States Navy: tokens:us,navy prob:0.991 score:1565298 perfect_match:False]
->Relation [name:military.armed_force.personnel, military.armed_force.personnel:
]
Variable [index:0]
->Relation [name:freebase.valuenotation.has_value, freebase.valuenotation.has_value:
RelationName: have=have
DerivationMatch: have=have
RelationNameSynonym: have=have:1.00,many=have:0.42]
Variable [index:1]
]
Simple Candidate Graph: QueryCandidate pattern:ERMRT
[United States Navy (m.07wg3)] -> [military.armed_force.personnel] -> [?0]
[?0] -> [freebase.valuenotation.has_value] -> [?1]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT count(?1) where {
SELECT ?1 where {
fb:m.07wg3 fb:military.armed_force.personnel ?0 .
?0 fb:freebase.valuenotation.has_value ?1 .
FILTER (?1 != fb:m.07wg3)
} LIMIT 30000}
Result: 8
Query: what are some object-oriented programming languages
Entity: (u'Object-oriented programming', 0.999987096885, 232499, False)
Entity: (u'Programming language', 0.982300081132, 18949, False)
Entity: (u'Language', 0.546601915644, 110409, False)
Entity: (u'Computer programming', 0.535864586069, 62728, False)
Entity: (u'Programming', 0.18876521462, 245, True)
TargetType: Other
Root Node: Programming language
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Programming language, Programming language: tokens:programming,languages prob:0.982 score:18949 perfect_match:False]
->Relation [name:type.object.name, type.object.name:
RelationName: object-oriented=object
RelationNameSynonym: object-oriented=object:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Programming language (m.05r20)] -> [type.object.name] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.05r20 fb:type.object.name ?0 .
FILTER (?0 != fb:m.05r20)
} LIMIT 300
Result: Programming language
Query: what are the books in the chronicles of narnia series
Entity: (u'The Chronicles of Narnia', 0.831933, 43405, False)
Entity: (u'The Chronicles of Narnia (Film series)', 0.168067, 17332, False)
Entity: (u'The Chronicles of Narnia', 1.0, 43405, False)
Entity: (u'The Chronicles of Narnia: Prince Caspian', 1.0, 1652, False)
Entity: (u'The Chronicles of Narnia', 1.0, 43405, False)
Entity: (u'The Books', 0.776898125835, 3045, True)
Entity: (u'Terminator: The Sarah Connor Chronicles', 0.512775368798, 47135, False)
Entity: (u'German federal election, March 1933', 0.348180888537, 0, False)
Entity: (u'The Chronicles (Southern rap Album)', 0.324758400181, 0, True)
Entity: (u'The Chronicles of Amber', 0.16237920009, 20286, False)
Entity: (u'Lewis Cass', 0.147169070805, 7645, False)
Entity: (u'Inthe', 0.143579278312, 0, True)
Entity: (u'Book (m/0bt_c3)', 0.659496685521, 299831, False)
Entity: (u'Books of Chronicles', 0.192183839637, 30619, False)
Entity: (u'Chronicles: Volume One', 0.105350964125, 1389, False)
TargetType: Other
Root Node: The Chronicles of Narnia
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:The Chronicles of Narnia, The Chronicles of Narnia: tokens:the,chronicles,of,narnia,series prob:0.832 score:43405 perfect_match:False]
->Relation [name:book.literary_series.author_s, book.literary_series.author_s:
RelationName: book=book
RelationContext: book:0.0309
RelationNameSynonym: book=literary:0.46,book=author:0.54]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[The Chronicles of Narnia (m.07k3w)] -> [book.literary_series.author_s] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.07k3w fb:book.literary_series.author_s ?0 .
FILTER (?0 != fb:m.07k3w)
} LIMIT 300
Result: C. S. Lewis (m.01wd02c)
Query: what decision did manny pacquiao vs. timothy bradley end with
Entity: (u'Manny Pacquiao vs. Timothy Bradley', 1.0, 4, True)
Entity: (u'Timothy Bradley', 0.999511582473, 14325, True)
Entity: (u'Manny Pacqui\xe1o', 0.997628984622, 260311, False)
Entity: (u'Decision-making', 0.237567736896, 16435, False)
TargetType: Other
Root Node: Manny Pacquiao vs. Timothy Bradley
Candidate Graph: QueryCandidate [pattern:ERT
Entity [name:Manny Pacquiao vs. Timothy Bradley, Manny Pacquiao vs. Timothy Bradley: tokens:manny,pacquiao,vs.,timothy,bradley prob:1.000 score:4 perfect_match:True]
->Relation [name:boxing.boxing_match.round_match_ended, boxing.boxing_match.round_match_ended:
RelationName: end=end
DerivationMatch: end=end
RelationNameSynonym: end=end:1.00]
Variable [index:0]
]
Simple Candidate Graph: QueryCandidate pattern:ERT
[Manny Pacquiao vs. Timothy Bradley (m.0j24b7h)] -> [boxing.boxing_match.round_match_ended] -> [?0]
SPARQL query: PREFIX fb: <http://rdf.freebase.com/ns/>
SELECT DISTINCT ?0 where {
fb:m.0j24b7h fb:boxing.boxing_match.round_match_ended ?0 .
FILTER (?0 != fb:m.0j24b7h)
} LIMIT 300
Result: 12