Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/entities
from IPython.core.display import Image, display
display(Image('ner-accuracy.png', width=500))
precision recall f1-score supportOTHER 1.00 1.00 1.00 498279 event 0.98 0.99 0.99 2217 law 0.99 0.99 0.99 1610
location 0.99 1.00 1.00 20194
- organization 0.99 0.99 0.99 26093
person 1.00 0.99 1.00 43377
- quantity 1.00 1.00 1.00 13180
time 0.99 1.00 0.99 12750
avg / total 1.00 1.00 1.00 617700
precision recall f1-score supportOTHER 1.00 1.00 1.00 498587 event 0.98 0.99 0.98 2212 law 1.00 0.99 0.99 1746
location 0.99 1.00 1.00 20387
- organization 0.99 1.00 1.00 25376
person 1.00 1.00 1.00 43158
- quantity 1.00 1.00 1.00 13581
time 0.99 1.00 0.99 12653
avg / total 1.00 1.00 1.00 617700
precision recall f1-score supportOTHER 1.00 1.00 1.00 497138 event 0.99 0.99 0.99 2331 law 0.99 0.99 0.99 1872
location 0.99 1.00 1.00 20671
- organization 0.99 1.00 0.99 25942
person 0.99 1.00 1.00 43511
- quantity 1.00 1.00 1.00 13376
time 1.00 1.00 1.00 12859
avg / total 1.00 1.00 1.00 617700
precision recall f1-score supportOTHER 1.00 1.00 1.00 497198 event 0.98 0.95 0.96 2381 law 0.99 0.97 0.98 1881
location 0.99 0.99 0.99 20305
- organization 0.99 0.98 0.98 26036
person 0.99 0.99 0.99 43470
- quantity 0.99 0.99 0.99 13608
time 0.98 0.99 0.98 12821
avg / total 1.00 1.00 1.00 617700
precision recall f1-score supportquantity 0.991 0.991 0.991 13891 location 0.987 0.989 0.988 20798 time 0.987 0.977 0.982 13264 person 0.993 0.987 0.990 43590
- organization 0.974 0.973 0.973 25426
- event 0.995 0.983 0.989 2417
law 0.994 0.988 0.991 1686
avg / total 0.987 0.983 0.985 121072
precision recall f1-score supportOTHER 1.00 1.00 1.00 497073 event 0.99 0.97 0.98 2426 law 1.00 0.99 0.99 1806
location 1.00 1.00 1.00 20176
- organization 1.00 1.00 1.00 26044
person 1.00 1.00 1.00 44346
- quantity 1.00 1.00 1.00 13155
time 0.99 1.00 1.00 12674
avg / total 1.00 1.00 1.00 617700
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/language-detection
display(Image('language-detection-accuracy.png', width=500))
precision recall f1-score support
- OTHER 0.98 0.99 0.99 9424
eng 1.00 0.99 0.99 9972 ind 1.00 0.99 0.99 11511 zlm 1.00 1.00 1.00 10679
micro avg 0.99 0.99 0.99 41586 macro avg 0.99 0.99 0.99 41586
weighted avg 0.99 0.99 0.99 41586
precision recall f1-score support
- OTHER 1.00 0.97 0.99 9424
eng 0.99 1.00 0.99 9972 ind 1.00 1.00 1.00 11511 zlm 0.99 1.00 0.99 10679
micro avg 0.99 0.99 0.99 41586 macro avg 0.99 0.99 0.99 41586
weighted avg 0.99 0.99 0.99 41586
precision recall f1-score support
- OTHER 0.97 0.99 0.98 9424
eng 0.99 0.99 0.99 9972 ind 1.00 0.99 0.99 11511 zlm 1.00 1.00 1.00 10679
micro avg 0.99 0.99 0.99 41586 macro avg 0.99 0.99 0.99 41586
weighted avg 0.99 0.99 0.99 41586
precision recall f1-score supportother 1.00 0.99 0.99 9445
english 1.00 1.00 1.00 9987
- indonesian 1.00 1.00 1.00 11518
malay 1.00 1.00 1.00 10636
- micro avg 1.00 1.00 1.00 41586
macro avg 1.00 1.00 1.00 41586
weighted avg 1.00 1.00 1.00 41586
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/pos
display(Image('pos-accuracy.png', width=500))
precision recall f1-score supportADJ 0.99 1.00 1.00 22663 ADP 1.00 1.00 1.00 60199 ADV 1.00 1.00 1.00 23633 AUX 1.00 1.00 1.00 5249
- CCONJ 1.00 1.00 1.00 18485
DET 1.00 1.00 1.00 19849
- NOUN 1.00 1.00 1.00 135031
NUM 1.00 1.00 1.00 21842
- PART 1.00 1.00 1.00 2900
PRON 1.00 1.00 1.00 23908
PROPN 1.00 1.00 1.00 113206 SCONJ 1.00 0.99 1.00 7304 SYM 1.00 1.00 1.00 1205 VERB 1.00 1.00 1.00 61222 X 0.97 0.99 0.98 154
avg / total 1.00 1.00 1.00 516850
precision recall f1-score supportADJ 0.99 0.99 0.99 22879 ADP 1.00 1.00 1.00 60063 ADV 1.00 0.99 1.00 23653 AUX 1.00 1.00 1.00 5295
- CCONJ 1.00 1.00 1.00 18395
DET 1.00 1.00 1.00 20088
- NOUN 1.00 1.00 1.00 134736
NUM 1.00 1.00 1.00 21938
- PART 0.99 1.00 0.99 3093
PRON 1.00 1.00 1.00 24060
PROPN 1.00 1.00 1.00 112859 SCONJ 0.99 0.99 0.99 7445 SYM 0.99 0.99 0.99 1219 VERB 1.00 1.00 1.00 60937 X 0.98 0.97 0.98 190
avg / total 1.00 1.00 1.00 516850
precision recall f1-score supportADJ 0.99 0.99 0.99 22649 ADP 1.00 1.00 1.00 60088 ADV 0.99 1.00 0.99 24031 AUX 1.00 1.00 1.00 5279
- CCONJ 1.00 1.00 1.00 18469
DET 1.00 1.00 1.00 20053
- NOUN 1.00 1.00 1.00 134614
NUM 1.00 1.00 1.00 21703
- PART 1.00 0.99 0.99 2956
PRON 1.00 1.00 1.00 23786
PROPN 1.00 1.00 1.00 113689 SCONJ 0.99 0.99 0.99 7315 SYM 1.00 1.00 1.00 1189 VERB 1.00 1.00 1.00 60827 X 0.97 0.99 0.98 202
avg / total 1.00 1.00 1.00 516850
precision recall f1-score support
- PRON 0.998 0.997 0.998 47911
DET 0.990 0.993 0.991 39932
NOUN 0.988 0.988 0.988 270045 VERB 0.997 0.997 0.997 122015
- PROPN 0.989 0.988 0.988 225893
ADP 0.997 0.998 0.997 120358 ADV 0.992 0.991 0.991 47753
- CCONJ 0.997 0.998 0.997 36696
NUM 0.993 0.995 0.994 43748 ADJ 0.985 0.988 0.986 45244
- PART 0.992 0.995 0.993 5975
AUX 1.000 1.000 1.000 10505
- SCONJ 0.994 0.987 0.990 14798
SYM 0.998 0.997 0.998 2483
micro avg 0.992 0.992 0.992 1033356 macro avg 0.994 0.994 0.994 1033356
weighted avg 0.992 0.992 0.992 1033356
precision recall f1-score supportADJ 0.98 0.98 0.98 22626 ADP 0.99 0.99 0.99 60045 ADV 0.97 0.98 0.98 23537 AUX 0.99 0.99 0.99 5195
- CCONJ 0.99 0.99 0.99 18357
DET 0.99 0.99 0.99 19762
- NOUN 0.99 0.99 0.99 134505
NUM 0.99 0.99 0.99 22083
- PART 0.97 0.97 0.97 2924
PRON 0.99 0.99 0.99 23783
PROPN 0.99 0.99 0.99 114144 SCONJ 0.96 0.95 0.95 7534 SYM 0.97 0.98 0.97 1335 VERB 0.99 0.99 0.99 60834 X 0.93 0.68 0.79 186
avg / total 0.99 0.99 0.99 516850
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/sentiment
display(Image('sentiment-accuracy.png', width=500))
precision recall f1-score supportnegative 0.79 0.81 0.80 70549 positive 0.79 0.77 0.78 64456
avg / total 0.79 0.79 0.79 135005
precision recall f1-score supportnegative 0.75 0.83 0.79 70558 positive 0.79 0.70 0.75 64447
micro avg 0.77 0.77 0.77 135005 macro avg 0.77 0.77 0.77 135005
weighted avg 0.77 0.77 0.77 135005
precision recall f1-score supportnegative 0.82 0.79 0.80 70629 positive 0.77 0.81 0.79 64376
avg / total 0.80 0.80 0.80 135005
precision recall f1-score supportnegative 0.75 0.76 0.75 70301 positive 0.73 0.71 0.72 63700
avg / total 0.74 0.74 0.74 134001
precision recall f1-score supportnegative 0.79 0.78 0.78 70568 positive 0.76 0.77 0.77 64437
micro avg 0.77 0.77 0.77 135005 macro avg 0.77 0.77 0.77 135005
weighted avg 0.77 0.77 0.77 135005
precision recall f1-score supportnegative 0.75 0.76 0.75 70301 positive 0.73 0.71 0.72 63700
avg / total 0.74 0.74 0.74 134001
precision recall f1-score supportnegative 0.81 0.80 0.80 70440 positive 0.78 0.79 0.79 64565
micro avg 0.80 0.80 0.80 135005 macro avg 0.80 0.80 0.80 135005
weighted avg 0.80 0.80 0.80 135005
precision recall f1-score supportnegative 0.79 0.79 0.79 70613 positive 0.77 0.77 0.77 64392
avg / total 0.78 0.78 0.78 135005
precision recall f1-score supportnegative 0.78 0.84 0.81 70720 positive 0.80 0.74 0.77 64129
micro avg 0.79 0.79 0.79 134849 macro avg 0.79 0.79 0.79 134849
weighted avg 0.79 0.79 0.79 134849
precision recall f1-score supportnegative 0.81 0.80 0.81 70356 positive 0.79 0.80 0.79 64493
micro avg 0.80 0.80 0.80 134849 macro avg 0.80 0.80 0.80 134849
weighted avg 0.80 0.80 0.80 134849
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/toxic
Labels are,
{0: 'toxic', 1: 'severe_toxic', 2: 'obscene', 3: 'threat', 4: 'insult', 5: 'identity_hate'}display(Image('toxic-accuracy.png', width=500))
precision recall f1-score support0 0.75 0.58 0.65 797 1 0.46 0.36 0.41 77 2 0.71 0.59 0.64 423 3 0.00 0.00 0.00 30 4 0.68 0.56 0.61 384 5 0.40 0.23 0.29 74
avg / total 0.69 0.54 0.60 1785
precision recall f1-score support0 0.77 0.61 0.68 787 1 1.00 0.08 0.14 92 2 0.75 0.66 0.71 432 3 0.44 0.19 0.27 21 4 0.68 0.61 0.65 400 5 0.57 0.05 0.09 79
avg / total 0.75 0.57 0.62 1811
precision recall f1-score support0 0.80 0.47 0.59 815 1 0.58 0.19 0.29 94 2 0.90 0.38 0.54 425 3 0.40 0.06 0.11 31 4 0.85 0.35 0.49 410 5 0.35 0.08 0.13 74
avg / total 0.80 0.39 0.52 1849
precision recall f1-score support0 0.69 0.56 0.62 751 1 0.68 0.20 0.31 86 2 0.84 0.48 0.61 412 3 1.00 0.04 0.07 28 4 0.70 0.55 0.62 356 5 0.57 0.27 0.36 60
avg / total 0.73 0.50 0.58 1693
precision recall f1-score support0 0.98 0.27 0.43 805 1 0.50 0.02 0.04 88 2 0.99 0.30 0.46 460 3 0.00 0.00 0.00 32 4 0.87 0.22 0.35 420 5 0.00 0.00 0.00 68
avg / total 0.88 0.24 0.38 1873
precision recall f1-score support0 0.81 0.52 0.63 805 1 0.44 0.35 0.39 88 2 0.76 0.49 0.59 460 3 0.00 0.00 0.00 32 4 0.68 0.47 0.56 420 5 0.15 0.09 0.11 68
avg / total 0.71 0.47 0.56 1873
precision recall f1-score support0 0.68 0.64 0.66 799 1 0.43 0.22 0.29 81 2 0.77 0.59 0.67 423 3 0.57 0.16 0.25 25 4 0.70 0.53 0.61 404 5 0.33 0.01 0.02 81
avg / total 0.68 0.55 0.60 1813
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/subjectivity
display(Image('subjectivity-accuracy.png', width=500))
precision recall f1-score supportnegative 0.82 0.83 0.82 983 positive 0.83 0.83 0.83 1010
micro avg 0.83 0.83 0.83 1993 macro avg 0.83 0.83 0.83 1993
weighted avg 0.83 0.83 0.83 1993
precision recall f1-score supportnegative 0.75 0.95 0.84 1024 positive 0.93 0.67 0.78 969
micro avg 0.82 0.82 0.82 1993 macro avg 0.84 0.81 0.81 1993
weighted avg 0.84 0.82 0.81 1993
precision recall f1-score supportnegative 0.82 0.89 0.85 989 positive 0.88 0.81 0.84 1004
micro avg 0.85 0.85 0.85 1993 macro avg 0.85 0.85 0.85 1993
weighted avg 0.85 0.85 0.85 1993
precision recall f1-score supportnegative 0.89 0.87 0.88 984 positive 0.87 0.89 0.88 1009
micro avg 0.88 0.88 0.88 1993 macro avg 0.88 0.88 0.88 1993
weighted avg 0.88 0.88 0.88 1993
precision recall f1-score supportnegative 0.88 0.91 0.89 1003 positive 0.90 0.87 0.89 990
micro avg 0.89 0.89 0.89 1993 macro avg 0.89 0.89 0.89 1993
weighted avg 0.89 0.89 0.89 1993
precision recall f1-score supportnegative 0.88 0.88 0.88 1002 positive 0.88 0.87 0.88 991
avg / total 0.88 0.88 0.88 1993
precision recall f1-score supportnegative 0.83 0.87 0.85 1017 positive 0.85 0.81 0.83 976
micro avg 0.84 0.84 0.84 1993 macro avg 0.84 0.84 0.84 1993
weighted avg 0.84 0.84 0.84 1993
precision recall f1-score supportnegative 0.85 0.78 0.81 987 positive 0.80 0.86 0.83 1006
micro avg 0.82 0.82 0.82 1993 macro avg 0.82 0.82 0.82 1993
weighted avg 0.82 0.82 0.82 1993
precision recall f1-score supportnegative 0.91 0.85 0.88 999 positive 0.86 0.92 0.89 994
micro avg 0.89 0.89 0.89 1993 macro avg 0.89 0.89 0.89 1993
weighted avg 0.89 0.89 0.89 1993
precision recall f1-score supportnegative 0.86 0.85 0.85 1003 positive 0.85 0.86 0.85 990
micro avg 0.85 0.85 0.85 1993 macro avg 0.85 0.85 0.85 1993
weighted avg 0.85 0.85 0.85 1993
Trained on 80% of dataset, tested on 20% of dataset. All training sessions stored in session/emotion
display(Image('emotion-accuracy.png', width=500))
precision recall f1-score support
- anger 0.80 0.80 0.80 3827
- fear 0.77 0.78 0.78 3760
joy 0.81 0.78 0.80 3958
love 0.82 0.86 0.84 3099
sadness 0.73 0.76 0.74 3119
surprise 0.79 0.74 0.77 1940
avg / total 0.79 0.79 0.79 19703
precision recall f1-score support
- anger 0.73 0.83 0.78 3747
- fear 0.70 0.84 0.77 3789
joy 0.74 0.80 0.77 3929
love 0.82 0.76 0.79 3081
sadness 0.82 0.60 0.69 3168
surprise 0.85 0.63 0.72 1989
avg / total 0.77 0.76 0.76 19703
precision recall f1-score support
- anger 0.81 0.80 0.81 3726
- fear 0.77 0.78 0.77 3806
joy 0.83 0.81 0.82 3975
love 0.86 0.83 0.85 2992
sadness 0.75 0.78 0.77 3293
surprise 0.77 0.79 0.78 1911
avg / total 0.80 0.80 0.80 19703
precision recall f1-score support
- anger 0.82 0.72 0.77 3717
- fear 0.72 0.77 0.75 3743
joy 0.77 0.74 0.76 4050
love 0.81 0.81 0.81 2992
sadness 0.71 0.74 0.72 3274
surprise 0.72 0.80 0.76 1927
avg / total 0.76 0.76 0.76 19703
precision recall f1-score support
- anger 0.82 0.75 0.78 3754
- fear 0.71 0.81 0.75 3837
joy 0.76 0.79 0.78 3844
love 0.83 0.83 0.83 3065
sadness 0.75 0.75 0.75 3241
surprise 0.79 0.64 0.71 1962
avg / total 0.77 0.77 0.77 19703
precision recall f1-score support
- anger 0.79 0.75 0.77 3803
- fear 0.73 0.73 0.73 3784
joy 0.71 0.77 0.74 3872
love 0.81 0.80 0.80 3052
sadness 0.72 0.70 0.71 3205
surprise 0.73 0.70 0.72 1987
avg / total 0.75 0.74 0.75 19703
precision recall f1-score support
- anger 0.81 0.79 0.80 3786
- fear 0.78 0.79 0.78 3754
joy 0.81 0.82 0.82 3886
love 0.85 0.84 0.85 3022
sadness 0.76 0.80 0.78 3300
surprise 0.81 0.75 0.78 1955
avg / total 0.80 0.80 0.80 19703
precision recall f1-score support
- anger 0.80 0.79 0.80 3774
- fear 0.78 0.75 0.77 3759
joy 0.79 0.80 0.79 3944
love 0.83 0.84 0.84 3033
sadness 0.75 0.75 0.75 3272
surprise 0.76 0.80 0.78 1921
avg / total 0.79 0.79 0.79 19703
precision recall f1-score support
- anger 0.72 0.82 0.77 3833
- fear 0.68 0.80 0.74 3802
joy 0.68 0.84 0.75 3924
love 0.85 0.71 0.78 2981
sadness 0.81 0.67 0.73 3189
surprise 0.80 0.36 0.50 1974
avg / total 0.75 0.73 0.73 19703
precision recall f1-score support
- anger 0.80 0.80 0.80 3769
- fear 0.79 0.76 0.78 3808
joy 0.79 0.81 0.80 3913
love 0.84 0.85 0.84 2998
sadness 0.76 0.75 0.76 3250
surprise 0.77 0.77 0.77 1965
avg / total 0.79 0.79 0.79 19703
Trained on 90% of dataset, tested on 10% of dataset. All training sessions stored in session/dependency
display(Image('dependency-accuracy.png', width=500))
precision recall f1-score supportPAD 1.0000 1.0000 1.0000 843055 acl 0.9406 0.9296 0.9351 2983
advcl 0.8924 0.8613 0.8766 1175
- advmod 0.9549 0.9482 0.9515 4712
amod 0.9296 0.9100 0.9197 4135
- appos 0.9312 0.9570 0.9439 2488
aux 1.0000 1.0000 1.0000 5
- case 0.9809 0.9823 0.9816 10557
cc 0.9676 0.9795 0.9735 3170
ccomp 0.8598 0.8045 0.8312 404
compound 0.9201 0.9464 0.9331 6605
- compound:plur 0.9597 0.9630 0.9613 594
- conj 0.9600 0.9572 0.9586 4158
cop 0.9670 0.9720 0.9695 966
- csubj 0.8929 0.8333 0.8621 30
- csubj:pass 0.8000 0.6667 0.7273 12
dep 0.8189 0.9259 0.8691 459 det 0.9558 0.9369 0.9463 4041
- fixed 0.9337 0.8953 0.9141 535
flat 0.9724 0.9714 0.9719 10479 iobj 0.9286 0.7222 0.8125 18 mark 0.9210 0.9491 0.9349 1376 nmod 0.9355 0.9324 0.9340 3921
nsubj 0.9430 0.9538 0.9484 6345
- nsubj:pass 0.9458 0.9053 0.9251 1985
- nummod 0.9762 0.9787 0.9775 3854
obj 0.9495 0.9465 0.9480 5162 obl 0.9458 0.9543 0.9500 5599
- parataxis 0.9268 0.8283 0.8748 367
- punct 0.9978 0.9968 0.9973 16549
root 0.9743 0.9643 0.9693 5037
xcomp 0.8878 0.9039 0.8958 1217
avg / total 0.9953 0.9953 0.9953 951993
precision recall f1-score support
0 1.0000 1.0000 1.0000 843055 1 0.9718 0.9633 0.9675 5037 2 0.9604 0.9459 0.9531 4285 3 0.9474 0.9557 0.9515 4971 4 0.9575 0.9647 0.9611 6594 5 0.9534 0.9665 0.9599 5880 6 0.9648 0.9632 0.9640 6037 7 0.9512 0.9654 0.9582 5548 8 0.9611 0.9623 0.9617 5542 9 0.9729 0.9498 0.9612 4877
10 0.9614 0.9621 0.9617 4559 11 0.9495 0.9588 0.9541 4316 12 0.9547 0.9573 0.9560 3698 13 0.9664 0.9506 0.9584 3600 14 0.9652 0.9590 0.9621 3294 15 0.9619 0.9541 0.9580 3179 16 0.9604 0.9573 0.9589 3117 17 0.9634 0.9587 0.9610 2831 18 0.9406 0.9594 0.9499 2392 19 0.9657 0.9582 0.9619 2176 20 0.9656 0.9615 0.9635 2102 21 0.9523 0.9577 0.9550 1960 22 0.9519 0.9586 0.9552 1859 23 0.9605 0.9555 0.9580 1732 24 0.9649 0.9474 0.9561 1540 25 0.9399 0.9503 0.9451 1349 26 0.9680 0.9333 0.9503 1199 27 0.9246 0.9604 0.9422 1111 28 0.9491 0.9561 0.9526 956 29 0.9578 0.9646 0.9612 989 30 0.9365 0.9513 0.9438 1007 31 0.9483 0.9592 0.9537 784 32 0.9352 0.9545 0.9448 726 33 0.9468 0.9290 0.9378 690 34 0.9575 0.9464 0.9519 690 35 0.9480 0.9231 0.9354 533 36 0.9532 0.9432 0.9481 475 37 0.9511 0.9340 0.9425 500 38 0.9455 0.9139 0.9294 418 39 0.9326 0.9708 0.9513 342 40 0.9361 0.9338 0.9350 408 41 0.9260 0.9602 0.9428 352 42 0.9649 0.9615 0.9632 286 43 0.9418 0.9487 0.9453 273 44 0.9125 0.9389 0.9255 311 45 0.9406 0.9556 0.9480 315 46 0.9703 0.9655 0.9679 203 47 0.9662 0.9542 0.9602 240 48 0.9065 0.9065 0.9065 214 49 0.9455 0.9720 0.9585 214 50 0.9315 0.9189 0.9252 148 51 0.9356 0.9265 0.9310 204 52 0.9257 0.9580 0.9416 143 53 0.9496 0.9231 0.9362 143 54 0.9381 0.9430 0.9406 193 55 0.9837 0.9237 0.9528 131 56 0.8532 0.9688 0.9073 96 57 0.9604 0.9510 0.9557 102 58 0.9633 0.9459 0.9545 111 59 0.9870 0.8837 0.9325 86 60 1.0000 0.9559 0.9774 68 61 0.9429 0.9519 0.9474 104 62 0.9726 0.8875 0.9281 80 63 0.9459 0.9589 0.9524 73 64 0.9385 0.9531 0.9457 64 65 1.0000 0.8833 0.9381 60 66 0.8676 0.9516 0.9077 62 67 0.9020 0.8519 0.8762 54 68 0.9683 0.9242 0.9457 66 69 0.9474 0.9351 0.9412 77 70 0.8406 0.8923 0.8657 65 71 0.9474 0.9818 0.9643 55 72 0.9722 0.9459 0.9589 37 73 0.9796 0.9600 0.9697 50 74 0.9630 0.9630 0.9630 27 75 0.9750 1.0000 0.9873 39 76 0.9655 1.0000 0.9825 28 77 0.9655 0.9333 0.9492 30 78 1.0000 1.0000 1.0000 24 79 0.9677 1.0000 0.9836 30 80 0.9608 0.9074 0.9333 54 81 0.9167 1.0000 0.9565 11 82 0.9074 0.9423 0.9245 52 83 0.9259 1.0000 0.9615 25 84 0.9677 1.0000 0.9836 30 85 1.0000 1.0000 1.0000 14 86 1.0000 0.9412 0.9697 34 87 1.0000 1.0000 1.0000 22 88 1.0000 1.0000 1.0000 8 89 1.0000 1.0000 1.0000 14 90 1.0000 1.0000 1.0000 18 91 0.9677 0.8824 0.9231 34 92 0.8182 1.0000 0.9000 9 93 0.9444 0.9444 0.9444 18 94 1.0000 0.9444 0.9714 18 95 0.9259 0.9615 0.9434 26 96 1.0000 1.0000 1.0000 8 97 1.0000 1.0000 1.0000 2 98 1.0000 1.0000 1.0000 16 99 0.9697 0.8649 0.9143 37
100 1.0000 1.0000 1.0000 2 101 1.0000 1.0000 1.0000 44 102 1.0000 1.0000 1.0000 15 103 0.8889 1.0000 0.9412 8 104 0.8269 0.9773 0.8958 44 105 1.0000 1.0000 1.0000 6 106 1.0000 1.0000 1.0000 7 107 1.0000 1.0000 1.0000 10 108 0.9412 1.0000 0.9697 32 109 1.0000 1.0000 1.0000 13 110 1.0000 1.0000 1.0000 9 111 1.0000 1.0000 1.0000 1 112 1.0000 0.7826 0.8780 23 113 1.0000 1.0000 1.0000 16 114 0.8333 1.0000 0.9091 5 115 1.0000 1.0000 1.0000 1 116 0.9130 0.9545 0.9333 22 117 1.0000 1.0000 1.0000 5 118 0.0000 0.0000 0.0000 0 119 1.0000 1.0000 1.0000 3 120 1.0000 1.0000 1.0000 15 122 1.0000 1.0000 1.0000 8 123 1.0000 1.0000 1.0000 4 125 1.0000 1.0000 1.0000 10 126 1.0000 1.0000 1.0000 2 129 1.0000 1.0000 1.0000 8 133 1.0000 1.0000 1.0000 4 135 1.0000 1.0000 1.0000 3 136 1.0000 1.0000 1.0000 2 139 1.0000 1.0000 1.0000 1 142 1.0000 1.0000 1.0000 2 146 1.0000 1.0000 1.0000 1 151 1.0000 1.0000 1.0000 1
avg / total 0.9951 0.9951 0.9951 951993
precision recall f1-score supportPAD 1.0000 1.0000 1.0000 840905 acl 0.9249 0.9392 0.9320 3094
advcl 0.8952 0.8478 0.8709 1209
- advmod 0.9629 0.9475 0.9551 4952
amod 0.9288 0.9246 0.9267 4218
- appos 0.9535 0.9204 0.9367 2426
aux 1.0000 1.0000 1.0000 1
- case 0.9796 0.9795 0.9796 10991
cc 0.9686 0.9739 0.9713 3298
ccomp 0.8426 0.8501 0.8463 447
compound 0.9170 0.9477 0.9321 6787
- compound:plur 0.9428 0.9744 0.9584 626
- conj 0.9539 0.9581 0.9560 4251
cop 0.9625 0.9809 0.9716 993
- csubj 0.9655 0.8750 0.9180 32
- csubj:pass 1.0000 0.9167 0.9565 12
dep 0.8905 0.8320 0.8603 518 det 0.9503 0.9364 0.9433 4088
- fixed 0.9113 0.8899 0.9005 554
flat 0.9596 0.9792 0.9693 10272 iobj 1.0000 0.6000 0.7500 15 mark 0.9396 0.9217 0.9305 1417 nmod 0.9086 0.9475 0.9277 4155
nsubj 0.9524 0.9547 0.9535 6483
- nsubj:pass 0.9402 0.9108 0.9252 1916
- nummod 0.9747 0.9761 0.9754 4022
obj 0.9559 0.9468 0.9513 5337 obl 0.9622 0.9242 0.9428 5727
- parataxis 0.8072 0.8910 0.8470 376
- punct 0.9972 0.9984 0.9978 16581
root 0.9646 0.9688 0.9667 5037
xcomp 0.9225 0.8364 0.8774 1253
avg / total 0.9950 0.9950 0.9950 951993
precision recall f1-score support
0 1.0000 1.0000 1.0000 840905 1 0.9709 0.9726 0.9717 5037 2 0.9310 0.9534 0.9420 4271 3 0.9543 0.9485 0.9514 5148 4 0.9587 0.9514 0.9551 6220 5 0.9471 0.9631 0.9550 5984 6 0.9593 0.9585 0.9589 5827 7 0.9597 0.9554 0.9576 5789 8 0.9657 0.9527 0.9592 5559 9 0.9548 0.9517 0.9532 5088
10 0.9565 0.9492 0.9528 4427 11 0.9458 0.9631 0.9544 4280 12 0.9584 0.9540 0.9562 3910 13 0.9481 0.9586 0.9533 3791 14 0.9385 0.9563 0.9473 3272 15 0.9577 0.9389 0.9482 3306 16 0.9383 0.9560 0.9471 3023 17 0.9629 0.9417 0.9522 2815 18 0.9384 0.9548 0.9465 2409 19 0.9463 0.9391 0.9427 2103 20 0.9349 0.9617 0.9481 2166 21 0.9712 0.9354 0.9530 2090 22 0.9525 0.9450 0.9487 1763 23 0.9512 0.9512 0.9512 1742 24 0.9624 0.9475 0.9549 1619 25 0.9439 0.9460 0.9449 1333 26 0.9584 0.9333 0.9457 1260 27 0.9443 0.9231 0.9336 1158 28 0.9384 0.9414 0.9399 955 29 0.9313 0.9417 0.9365 1080 30 0.9332 0.9323 0.9327 1004 31 0.9240 0.9404 0.9322 789 32 0.9500 0.9226 0.9361 762 33 0.9292 0.9502 0.9396 843 34 0.9553 0.9468 0.9510 677 35 0.9284 0.9396 0.9339 662 36 0.9238 0.9287 0.9262 561 37 0.9213 0.9152 0.9183 448 38 0.8978 0.9114 0.9045 395 39 0.8991 0.9114 0.9052 440 40 0.9262 0.9446 0.9353 505 41 0.9289 0.9098 0.9193 388 42 0.9544 0.9181 0.9359 342 43 0.9119 0.9308 0.9212 289 44 0.9106 0.9006 0.9056 362 45 0.8525 0.9091 0.8799 286 46 0.9283 0.8859 0.9066 263 47 0.9068 0.8924 0.8995 316 48 0.9282 0.9095 0.9188 199 49 0.9648 0.9202 0.9419 238 50 0.9274 0.9583 0.9426 120 51 0.9167 0.9585 0.9371 241 52 0.9507 0.9415 0.9461 205 53 0.9248 0.9179 0.9213 134 54 0.9200 0.9306 0.9253 173 55 0.9329 0.8910 0.9115 156 56 0.9073 0.8954 0.9013 153 57 0.9304 0.9469 0.9386 113 58 0.9417 0.9576 0.9496 118 59 0.8947 0.8500 0.8718 100 60 0.9770 0.8095 0.8854 105 61 0.8020 0.9576 0.8729 165 62 0.8767 0.8889 0.8828 72 63 0.9355 0.8365 0.8832 104 64 0.8852 0.8308 0.8571 65 65 0.9375 0.8955 0.9160 67 66 0.8690 0.8588 0.8639 85 67 0.9839 0.8472 0.9104 72 68 0.9223 0.9500 0.9360 100 69 0.9367 0.9250 0.9308 80 70 0.8442 0.9701 0.9028 67 71 0.8462 0.8462 0.8462 65 72 0.9200 0.8734 0.8961 79 73 0.8909 0.8596 0.8750 57 74 0.9487 0.8810 0.9136 42 75 0.9296 0.8919 0.9103 74 76 0.8333 0.9677 0.8955 31 77 0.8056 0.9062 0.8529 32 78 0.8750 0.8077 0.8400 26 79 0.7636 0.9333 0.8400 45 80 0.9180 0.8889 0.9032 63 81 0.7188 0.8214 0.7667 28 82 0.8983 0.9298 0.9138 57 83 1.0000 0.8571 0.9231 28 84 0.8605 0.9487 0.9024 39 85 0.9474 0.9474 0.9474 19 86 0.8919 0.9706 0.9296 34 87 0.9231 0.8571 0.8889 14 88 0.9474 0.7826 0.8571 23 89 1.0000 0.8571 0.9231 14 90 0.8929 0.8621 0.8772 29 91 0.8462 0.9429 0.8919 35 92 0.9333 0.7568 0.8358 37 93 0.7895 0.8333 0.8108 18 94 1.0000 0.8000 0.8889 20 95 0.9048 0.9500 0.9268 20 96 0.9412 0.9412 0.9412 17 97 0.9583 1.0000 0.9787 23 98 0.9000 1.0000 0.9474 9 99 1.0000 0.9643 0.9818 28
100 0.8333 1.0000 0.9091 5 101 1.0000 0.9231 0.9600 13 102 1.0000 1.0000 1.0000 13 103 0.8750 1.0000 0.9333 14 104 1.0000 0.9231 0.9600 26 105 1.0000 0.9167 0.9565 12 106 0.9444 0.8500 0.8947 20 107 1.0000 0.8571 0.9231 21 108 1.0000 1.0000 1.0000 20 109 1.0000 1.0000 1.0000 6 110 0.8750 1.0000 0.9333 7 111 1.0000 1.0000 1.0000 4 112 0.9200 0.9583 0.9388 24 113 0.8889 1.0000 0.9412 8 114 1.0000 0.6667 0.8000 3 115 1.0000 1.0000 1.0000 5 116 0.9474 0.8571 0.9000 21 117 0.6667 1.0000 0.8000 2 119 1.0000 1.0000 1.0000 3 120 0.8824 0.9375 0.9091 16 121 1.0000 0.8000 0.8889 5 122 0.8889 1.0000 0.9412 8 123 0.0000 0.0000 0.0000 2 124 1.0000 0.6667 0.8000 3 125 1.0000 1.0000 1.0000 8 126 1.0000 0.8000 0.8889 10 127 1.0000 1.0000 1.0000 3 128 1.0000 1.0000 1.0000 1 129 1.0000 1.0000 1.0000 5 130 1.0000 0.8333 0.9091 12 131 1.0000 1.0000 1.0000 2 132 1.0000 1.0000 1.0000 1 133 1.0000 1.0000 1.0000 9 134 1.0000 1.0000 1.0000 6 136 1.0000 1.0000 1.0000 3 137 1.0000 1.0000 1.0000 10 138 1.0000 1.0000 1.0000 10 140 1.0000 1.0000 1.0000 4 141 1.0000 1.0000 1.0000 2 142 0.4000 0.5000 0.4444 4 144 0.5714 1.0000 0.7273 4 146 0.7500 0.7500 0.7500 4 147 1.0000 0.6000 0.7500 5 149 1.0000 1.0000 1.0000 2 150 0.6667 0.6667 0.6667 3 151 0.5000 0.5000 0.5000 2 152 0.5000 0.5000 0.5000 2 153 1.0000 0.5000 0.6667 2 156 1.0000 1.0000 1.0000 2 158 0.8889 1.0000 0.9412 8 160 0.8000 1.0000 0.8889 4 164 1.0000 1.0000 1.0000 4
avg / total 0.9941 0.9941 0.9941 951993
precision recall f1-score supportPAD 1.0000 1.0000 1.0000 841717 acl 0.9501 0.9110 0.9301 2965
advcl 0.8127 0.8719 0.8413 1249
- advmod 0.9423 0.9329 0.9376 4846
amod 0.9141 0.9104 0.9123 4208
- appos 0.9282 0.9266 0.9274 2412
- case 0.9757 0.9756 0.9756 10896
cc 0.9613 0.9726 0.9669 3171
ccomp 0.8115 0.7094 0.7570 437
compound 0.9176 0.9350 0.9263 6804
- compound:plur 0.9172 0.9767 0.9460 601
- conj 0.9504 0.9493 0.9498 4119
cop 0.9621 0.9761 0.9690 962
- csubj 0.8095 0.7083 0.7556 24
- csubj:pass 0.7500 0.6000 0.6667 10
dep 0.8712 0.8333 0.8519 552 det 0.9288 0.9339 0.9313 4082
- fixed 0.9229 0.8288 0.8733 549
flat 0.9619 0.9712 0.9666 10328 iobj 0.7273 0.8000 0.7619 10 mark 0.9059 0.9260 0.9159 1487 nmod 0.9159 0.9318 0.9238 4105
nsubj 0.9284 0.9550 0.9415 6316
- nsubj:pass 0.9367 0.8999 0.9179 2007
- nummod 0.9743 0.9617 0.9680 4024
obj 0.9428 0.9340 0.9384 5184 obl 0.9598 0.9292 0.9442 5776
- parataxis 0.8301 0.7537 0.7900 337
- punct 0.9957 0.9984 0.9971 16529
root 0.9654 0.9694 0.9674 5037
xcomp 0.8955 0.8575 0.8761 1249
avg / total 0.9943 0.9943 0.9943 951993
precision recall f1-score support
0 1.0000 1.0000 1.0000 841717 1 0.9638 0.9676 0.9657 5037 2 0.9526 0.9295 0.9409 4367 3 0.9410 0.9395 0.9403 4942 4 0.9544 0.9516 0.9530 6440 5 0.9453 0.9514 0.9484 6035 6 0.9376 0.9633 0.9503 6024 7 0.9456 0.9491 0.9473 5398 8 0.9506 0.9438 0.9472 5482 9 0.9488 0.9455 0.9472 4977
10 0.9331 0.9578 0.9453 4430 11 0.9453 0.9468 0.9460 4583 12 0.9364 0.9420 0.9392 3673 13 0.9495 0.9298 0.9395 3719 14 0.9425 0.9343 0.9384 3316 15 0.9460 0.9197 0.9327 3065 16 0.9125 0.9443 0.9281 3071 17 0.9350 0.9228 0.9289 2667 18 0.9377 0.9198 0.9286 2469 19 0.9167 0.9267 0.9217 2197 20 0.9076 0.9286 0.9180 2031 21 0.9355 0.8701 0.9016 1917 22 0.8985 0.8980 0.8983 1834 23 0.9038 0.9011 0.9025 1689 24 0.9066 0.8968 0.9017 1667 25 0.8782 0.9227 0.8999 1320 26 0.8769 0.9204 0.8982 1169 27 0.9041 0.9049 0.9045 1094 28 0.9054 0.8825 0.8938 987 29 0.9352 0.8799 0.9067 1099 30 0.8952 0.9110 0.9031 910 31 0.8745 0.8951 0.8847 810 32 0.8978 0.8772 0.8874 741 33 0.8782 0.9206 0.8989 705 34 0.9467 0.8692 0.9063 818 35 0.8893 0.8745 0.8819 542 36 0.9258 0.8794 0.9020 539 37 0.8603 0.9259 0.8919 459 38 0.9019 0.8458 0.8729 402 39 0.8577 0.9035 0.8800 487 40 0.8374 0.9071 0.8709 420 41 0.9148 0.8496 0.8810 379 42 0.8424 0.9393 0.8882 313 43 0.8852 0.8415 0.8628 284 44 0.9130 0.8571 0.8842 245 45 0.8829 0.9009 0.8918 343 46 0.8036 0.8654 0.8333 208 47 0.8803 0.8834 0.8818 283 48 0.9158 0.7699 0.8365 226 49 0.9074 0.8376 0.8711 234 50 0.7014 0.9136 0.7936 162 51 0.8268 0.9080 0.8655 163 52 0.8539 0.8889 0.8711 171 53 0.9136 0.8457 0.8783 175 54 0.8881 0.8581 0.8729 148 55 0.9073 0.8354 0.8698 164 56 0.8456 0.9200 0.8812 125 57 0.9000 0.8250 0.8609 120 58 0.9027 0.8430 0.8718 121 59 0.7947 0.9231 0.8541 130 60 0.7705 0.7833 0.7769 60 61 0.9315 0.8774 0.9037 155 62 0.8611 0.8493 0.8552 73 63 0.8172 0.9048 0.8588 84 64 0.8571 0.7273 0.7869 66 65 0.9130 0.8750 0.8936 72 66 0.7500 0.9398 0.8342 83 67 0.8409 0.8315 0.8362 89 68 0.9545 0.7590 0.8456 83 69 0.8916 0.8810 0.8862 84 70 0.7727 0.8644 0.8160 59 71 0.8679 0.8846 0.8762 52 72 0.8876 0.8404 0.8634 94 73 0.9298 0.8833 0.9060 60 74 0.9273 0.8226 0.8718 62 75 0.9070 0.8298 0.8667 47 76 0.7885 0.8723 0.8283 47 77 0.8000 0.8780 0.8372 41 78 0.8542 1.0000 0.9213 41 79 0.8696 0.9091 0.8889 44 80 0.9375 0.8571 0.8955 70 81 0.8667 0.7222 0.7879 36 82 0.8514 0.9130 0.8811 69 83 0.9024 0.9250 0.9136 40 84 0.9444 1.0000 0.9714 34 85 0.9189 0.9444 0.9315 36 86 0.8810 0.9487 0.9136 39 87 0.9310 0.8710 0.9000 31 88 0.8857 1.0000 0.9394 31 89 0.9200 0.9200 0.9200 25 90 0.8667 0.8125 0.8387 32 91 0.8519 0.9200 0.8846 25 92 0.8913 0.9535 0.9213 43 93 0.8500 0.9444 0.8947 18 94 0.9231 0.8571 0.8889 28 95 0.7500 0.8571 0.8000 7 96 0.9375 0.7143 0.8108 21 97 0.9688 0.8158 0.8857 38 98 0.9091 0.8696 0.8889 23 99 0.8462 1.0000 0.9167 33
100 1.0000 0.7778 0.8750 9 101 0.9744 0.9744 0.9744 39 102 0.8636 0.8636 0.8636 22 103 0.9677 0.9677 0.9677 31 104 1.0000 1.0000 1.0000 7 105 1.0000 0.6471 0.7857 17 106 0.9600 1.0000 0.9796 24 107 0.9750 1.0000 0.9873 39 108 0.8947 1.0000 0.9444 17 109 1.0000 1.0000 1.0000 14 110 0.9524 1.0000 0.9756 20 111 0.9091 0.8333 0.8696 12 112 0.9259 0.9259 0.9259 27 113 0.8889 1.0000 0.9412 16 114 0.8000 0.9231 0.8571 13 115 0.8235 1.0000 0.9032 14 116 1.0000 0.8095 0.8947 21 117 1.0000 0.8571 0.9231 7 118 0.7692 0.8333 0.8000 12 119 1.0000 1.0000 1.0000 4 120 0.9500 1.0000 0.9744 19 121 1.0000 1.0000 1.0000 7 122 0.8235 0.9333 0.8750 15 123 1.0000 1.0000 1.0000 6 124 1.0000 0.3333 0.5000 3 125 1.0000 0.8889 0.9412 18 126 1.0000 0.9667 0.9831 30 127 0.8750 1.0000 0.9333 7 128 0.8333 0.8333 0.8333 6 129 0.9412 0.9412 0.9412 17 130 0.9333 1.0000 0.9655 14 131 1.0000 1.0000 1.0000 9 132 1.0000 1.0000 1.0000 3 133 1.0000 1.0000 1.0000 11 134 0.9412 1.0000 0.9697 16 135 1.0000 1.0000 1.0000 6 136 1.0000 0.8000 0.8889 10 137 1.0000 0.8000 0.8889 10 138 1.0000 1.0000 1.0000 22 139 0.0000 0.0000 0.0000 1 140 1.0000 1.0000 1.0000 2 141 1.0000 1.0000 1.0000 2 142 1.0000 1.0000 1.0000 4 144 1.0000 1.0000 1.0000 4 146 1.0000 1.0000 1.0000 3 147 0.8889 1.0000 0.9412 8 149 1.0000 1.0000 1.0000 4 150 0.7500 1.0000 0.8571 3 151 1.0000 1.0000 1.0000 2 152 1.0000 1.0000 1.0000 1 153 1.0000 1.0000 1.0000 1 154 1.0000 1.0000 1.0000 2 156 1.0000 0.8333 0.9091 6 157 1.0000 1.0000 1.0000 1 158 1.0000 1.0000 1.0000 5 159 1.0000 1.0000 1.0000 1 160 1.0000 1.0000 1.0000 2 162 1.0000 1.0000 1.0000 3 163 0.0000 0.0000 0.0000 2 164 1.0000 1.0000 1.0000 2 167 0.6667 1.0000 0.8000 4 174 1.0000 1.0000 1.0000 2 176 1.0000 0.7500 0.8571 4 177 1.0000 1.0000 1.0000 2 178 1.0000 1.0000 1.0000 1 179 1.0000 1.0000 1.0000 1 182 1.0000 1.0000 1.0000 4 183 1.0000 1.0000 1.0000 4
avg / total 0.9921 0.9920 0.9920 951993
precision recall f1-score supportPAD 1.0000 1.0000 1.0000 841796 acl 0.8768 0.8849 0.8809 3016
advcl 0.8290 0.7943 0.8113 1196
- advmod 0.9043 0.9163 0.9102 4754
amod 0.9121 0.8773 0.8943 4149
- appos 0.8934 0.8983 0.8958 2547
aux 1.0000 1.0000 1.0000 6
- case 0.9593 0.9670 0.9631 10888
cc 0.9523 0.9606 0.9564 3198
ccomp 0.7984 0.7385 0.7673 413
compound 0.8677 0.8956 0.8815 6679
- compound:plur 0.9073 0.9255 0.9163 550
- conj 0.8625 0.9330 0.8964 4162
cop 0.9296 0.9679 0.9484 996
- csubj 0.9000 0.4091 0.5625 22
- csubj:pass 0.8462 0.8462 0.8462 13
dep 0.8274 0.7377 0.7800 507 det 0.8897 0.9196 0.9044 4094
- fixed 0.8851 0.7966 0.8385 580
flat 0.9468 0.9198 0.9331 10333 iobj 1.0000 0.6000 0.7500 20 mark 0.8535 0.8447 0.8491 1359 nmod 0.8749 0.8907 0.8827 4107
nsubj 0.8746 0.8881 0.8813 6471
- nsubj:pass 0.8478 0.7116 0.7738 1949
- nummod 0.9568 0.9524 0.9546 3884
obj 0.9082 0.8946 0.9013 5274 obl 0.9203 0.8854 0.9025 5740
- parataxis 0.7980 0.7980 0.7980 391
- punct 0.9933 0.9957 0.9945 16561
root 0.8974 0.9200 0.9085 5037
xcomp 0.8580 0.8593 0.8587 1301
avg / total 0.9906 0.9906 0.9906 951993
precision recall f1-score support
0 1.0000 1.0000 1.0000 841796 1 0.9486 0.9277 0.9381 5037 2 0.9157 0.9547 0.9348 4325 3 0.9505 0.9137 0.9318 4856 4 0.9439 0.9311 0.9374 6309 5 0.9422 0.9396 0.9409 6540 6 0.9314 0.9516 0.9414 5697 7 0.9468 0.9461 0.9464 5414 8 0.9524 0.9394 0.9458 5559 9 0.9432 0.9421 0.9427 5028
10 0.9308 0.9544 0.9425 4300 11 0.9623 0.9323 0.9471 4358 12 0.9449 0.9493 0.9471 3903 13 0.9338 0.9442 0.9390 3497 14 0.9444 0.9475 0.9459 3445 15 0.9445 0.9487 0.9466 3177 16 0.9411 0.9589 0.9500 3068 17 0.9350 0.9589 0.9468 2774 18 0.9527 0.9352 0.9439 2499 19 0.9767 0.9207 0.9478 2319 20 0.9445 0.9558 0.9501 2013 21 0.9321 0.9374 0.9347 2124 22 0.9337 0.9423 0.9380 1749 23 0.9508 0.9175 0.9339 1685 24 0.9608 0.9240 0.9421 1540 25 0.8654 0.9661 0.9130 1358 26 0.9511 0.9245 0.9376 1179 27 0.9416 0.9367 0.9392 1154 28 0.8961 0.9549 0.9245 975 29 0.9260 0.9383 0.9321 1054 30 0.9342 0.9551 0.9445 1025 31 0.9482 0.9146 0.9311 761 32 0.9549 0.9126 0.9333 835 33 0.9235 0.9506 0.9368 749 34 0.9492 0.9465 0.9478 710 35 0.9323 0.9649 0.9483 599 36 0.9750 0.9458 0.9602 535 37 0.9363 0.9620 0.9490 474 38 0.9099 0.9815 0.9443 432 39 0.9462 0.9342 0.9401 395 40 0.9170 0.9535 0.9349 452 41 0.9446 0.9214 0.9328 407 42 0.9452 0.9452 0.9452 292 43 0.9731 0.9031 0.9368 320 44 0.9030 0.9767 0.9384 343 45 0.9343 0.9812 0.9572 319 46 0.9943 0.7955 0.8838 220 47 0.9420 0.9684 0.9550 285 48 0.9160 0.9745 0.9443 235 49 0.9113 0.9893 0.9487 187 50 0.9568 0.8636 0.9078 154 51 0.9706 0.9538 0.9621 173 52 0.9554 0.9934 0.9740 151 53 0.9116 0.9515 0.9311 206 54 0.9008 0.9833 0.9402 120 55 0.9371 0.9371 0.9371 159 56 0.9179 0.9535 0.9354 129 57 0.9091 0.8824 0.8955 102 58 0.9350 0.9127 0.9237 126 59 0.9725 0.7910 0.8724 134 60 0.9576 0.9826 0.9700 115 61 0.9200 0.9485 0.9340 97 62 0.9200 0.9079 0.9139 76 63 0.9551 0.9770 0.9659 87 64 0.9878 0.9310 0.9586 87 65 0.9103 0.9861 0.9467 72 66 0.9474 0.9863 0.9664 73 67 1.0000 0.9667 0.9831 60 68 0.9855 0.8831 0.9315 77 69 0.8889 0.9231 0.9057 52 70 0.9524 1.0000 0.9756 80 71 0.9241 0.9605 0.9419 76 72 0.9870 0.9870 0.9870 77 73 0.9531 1.0000 0.9760 61 74 1.0000 0.9667 0.9831 30 75 0.9412 1.0000 0.9697 64 76 1.0000 0.8571 0.9231 28 77 0.9487 1.0000 0.9737 37 78 0.9677 0.9677 0.9677 31 79 1.0000 1.0000 1.0000 25 80 1.0000 0.9348 0.9663 46 81 1.0000 0.9756 0.9877 41 82 1.0000 0.9302 0.9639 43 83 0.9474 1.0000 0.9730 18 84 0.8846 1.0000 0.9388 23 85 0.9583 1.0000 0.9787 23 86 1.0000 0.8636 0.9268 44 87 1.0000 1.0000 1.0000 10 88 0.9412 0.9412 0.9412 17 89 1.0000 0.8750 0.9333 8 90 0.9167 0.9565 0.9362 23 91 1.0000 1.0000 1.0000 15 92 1.0000 1.0000 1.0000 34 93 0.8571 1.0000 0.9231 6 94 0.9231 1.0000 0.9600 12 95 1.0000 1.0000 1.0000 9 96 1.0000 0.9333 0.9655 15 97 1.0000 1.0000 1.0000 30 98 1.0000 1.0000 1.0000 8 99 1.0000 0.9200 0.9583 25
100 0.8571 1.0000 0.9231 6 101 1.0000 0.9744 0.9870 39 102 1.0000 1.0000 1.0000 7 103 0.8889 1.0000 0.9412 16 104 1.0000 0.9500 0.9744 20 105 1.0000 0.9000 0.9474 10 106 0.9500 1.0000 0.9744 19 107 0.7500 1.0000 0.8571 27 108 1.0000 1.0000 1.0000 15 109 1.0000 1.0000 1.0000 3 110 1.0000 1.0000 1.0000 14 111 1.0000 1.0000 1.0000 9 112 0.9474 1.0000 0.9730 18 113 0.8571 1.0000 0.9231 6 114 1.0000 1.0000 1.0000 10 115 1.0000 1.0000 1.0000 7 116 1.0000 0.9375 0.9677 16 117 1.0000 0.5000 0.6667 2 118 1.0000 1.0000 1.0000 12 119 1.0000 1.0000 1.0000 4 120 1.0000 0.9231 0.9600 13 121 1.0000 1.0000 1.0000 6 122 1.0000 1.0000 1.0000 3 123 1.0000 0.8333 0.9091 6 124 1.0000 1.0000 1.0000 2 125 1.0000 1.0000 1.0000 2 126 0.8846 1.0000 0.9388 23 127 1.0000 1.0000 1.0000 6 128 1.0000 1.0000 1.0000 5 129 1.0000 0.8333 0.9091 6 130 1.0000 1.0000 1.0000 12 131 1.0000 0.7143 0.8333 7 132 1.0000 1.0000 1.0000 2 133 1.0000 1.0000 1.0000 4 134 0.9000 0.9000 0.9000 10 135 0.8571 1.0000 0.9231 6 136 1.0000 1.0000 1.0000 7 137 1.0000 1.0000 1.0000 8 138 1.0000 1.0000 1.0000 12 139 1.0000 1.0000 1.0000 1 140 1.0000 1.0000 1.0000 2 141 1.0000 1.0000 1.0000 2 142 1.0000 1.0000 1.0000 4 144 1.0000 1.0000 1.0000 4 146 1.0000 1.0000 1.0000 3 147 1.0000 1.0000 1.0000 7 149 1.0000 1.0000 1.0000 2 150 1.0000 1.0000 1.0000 2 151 1.0000 1.0000 1.0000 2 152 1.0000 1.0000 1.0000 1 153 1.0000 1.0000 1.0000 1 154 1.0000 1.0000 1.0000 2 156 1.0000 1.0000 1.0000 6 157 1.0000 1.0000 1.0000 1 158 1.0000 1.0000 1.0000 5 159 1.0000 1.0000 1.0000 1 160 1.0000 1.0000 1.0000 2 162 0.6667 0.6667 0.6667 3 163 0.6667 1.0000 0.8000 2 164 1.0000 1.0000 1.0000 2 167 1.0000 0.7500 0.8571 4 174 1.0000 1.0000 1.0000 2 176 1.0000 1.0000 1.0000 4 177 1.0000 1.0000 1.0000 2 178 1.0000 1.0000 1.0000 1 179 1.0000 1.0000 1.0000 1 182 1.0000 1.0000 1.0000 4 183 1.0000 1.0000 1.0000 4
avg / total 0.9933 0.9932 0.9932 951993
precision recall f1-score support
- case 0.9584 0.9687 0.9635 11014
obl 0.8045 0.8274 0.8158 5810
- flat 0.9469 0.9551 0.9510 10648
cc 0.9538 0.9652 0.9595 3336
conj 0.8684 0.8482 0.8582 4560
punct 0.9848 0.9963 0.9905 17017
- nsubj:pass 0.8336 0.7640 0.7973 2059
root 0.7960 0.8453 0.8199 5037
- nummod 0.9334 0.9359 0.9347 4088
mark 0.8739 0.8865 0.8802 1392
- advcl 0.7649 0.6508 0.7033 1200
- advmod 0.8932 0.8924 0.8928 4769
nmod 0.7762 0.7355 0.7553 4215
- nsubj 0.8600 0.8835 0.8716 6388
det 0.9020 0.8868 0.8943 4142
- compound 0.8776 0.8974 0.8874 6869
- amod 0.8677 0.8530 0.8602 4128
obj 0.8749 0.8765 0.8757 5256 acl 0.8375 0.8094 0.8232 3075
- xcomp 0.8082 0.8070 0.8076 1264
- parataxis 0.7636 0.6208 0.6848 385
- appos 0.8221 0.8177 0.8199 2425
cop 0.9350 0.9498 0.9423 1015
fixed 0.8569 0.8056 0.8305 602 ccomp 0.7516 0.5576 0.6402 434
- compound:plur 0.9154 0.9498 0.9323 638
dep 0.7820 0.5275 0.6300 510
- csubj 0.8750 0.8400 0.8571 25
iobj 0.9375 0.6818 0.7895 22
- csubj:pass 1.0000 0.8000 0.8889 5
aux 0.5000 0.2500 0.3333 4
avg / total 0.8953 0.8961 0.8953 112332
precision recall f1-score support
5 0.5452 0.5875 0.5656 5964 2 0.6193 0.7164 0.6643 4365 1 0.8839 0.9031 0.8934 4942 7 0.5181 0.5460 0.5317 5505 9 0.5569 0.5504 0.5536 4804
12 0.5421 0.5309 0.5364 3760 15 0.5556 0.5105 0.5321 3181 4 0.5195 0.6219 0.5661 6241 6 0.5346 0.5571 0.5456 5942 11 0.5350 0.5581 0.5463 4150 14 0.5425 0.5109 0.5262 3251 8 0.5463 0.5414 0.5438 5395 10 0.5705 0.5252 0.5469 4682 13 0.5506 0.5199 0.5348 3537 3 0.5871 0.6077 0.5972 5068 18 0.5613 0.5232 0.5415 2504 20 0.5772 0.5315 0.5534 2109 23 0.6065 0.5814 0.5937 1689 26 0.5820 0.5861 0.5841 1138 29 0.6089 0.5874 0.5980 1047 32 0.6459 0.6241 0.6348 798 35 0.6659 0.5931 0.6274 521 36 0.6312 0.6406 0.6359 537 40 0.6039 0.6620 0.6316 426 17 0.5513 0.5303 0.5406 2674 22 0.5889 0.5238 0.5545 1827 25 0.5898 0.5967 0.5932 1381 27 0.5802 0.5588 0.5693 1088 28 0.6101 0.6082 0.6092 970 34 0.6011 0.6029 0.6020 695 39 0.6711 0.5884 0.6270 430 37 0.6675 0.5876 0.6250 468 42 0.6975 0.6323 0.6633 310 43 0.6504 0.6584 0.6544 243 44 0.7205 0.6221 0.6677 344 47 0.6667 0.7077 0.6866 260 49 0.6903 0.7290 0.7091 214 51 0.6829 0.7368 0.7089 190 53 0.7483 0.6730 0.7086 159 55 0.7143 0.6936 0.7038 173 57 0.7093 0.6224 0.6630 98 59 0.7652 0.6779 0.7189 149 60 0.7253 0.7174 0.7213 92 61 0.7658 0.7516 0.7586 161 62 0.6500 0.5571 0.6000 70 63 0.7257 0.7736 0.7489 106 64 0.8730 0.7971 0.8333 69 65 0.8533 0.6667 0.7485 96 66 0.7097 0.8354 0.7674 79 67 0.5965 0.6415 0.6182 53 72 0.9362 0.6769 0.7857 65 70 0.9024 0.5968 0.7184 62 75 0.9348 0.7414 0.8269 58 77 0.7838 0.8286 0.8056 35 78 0.8750 0.8750 0.8750 16 80 0.7200 0.8000 0.7579 45 82 0.7027 0.7222 0.7123 36 83 0.6923 0.7200 0.7059 25 84 0.7407 0.5000 0.5970 40 85 0.6923 0.8571 0.7660 21 86 0.9091 0.6061 0.7273 33 87 0.5833 0.5000 0.5385 28 88 0.8333 0.4412 0.5769 34 89 0.7619 0.9412 0.8421 17 90 0.9143 0.7805 0.8421 41 91 0.6923 0.8182 0.7500 22 92 1.0000 0.8519 0.9200 27 93 1.0000 0.7273 0.8421 22 94 0.9333 0.6364 0.7568 22 95 1.0000 0.6250 0.7692 16 96 0.8000 0.6857 0.7385 35 97 0.9500 0.8261 0.8837 23
100 1.0000 0.6667 0.8000 6 103 1.0000 0.7857 0.8800 14 104 1.0000 0.6000 0.7500 15 101 0.9574 0.8491 0.9000 53 107 0.8846 0.8214 0.8519 28 112 0.8000 0.8000 0.8000 10 115 1.0000 0.5556 0.7143 9 120 0.6667 0.6667 0.6667 6 122 0.5556 0.7143 0.6250 7 124 1.0000 0.2857 0.4444 7 125 0.2857 0.4000 0.3333 5 126 0.5455 0.3529 0.4286 17 127 0.6667 1.0000 0.8000 4 128 1.0000 0.3500 0.5185 20 129 0.7000 0.7778 0.7368 9 130 0.8667 0.9286 0.8966 14 132 1.0000 0.7143 0.8333 7 133 0.5714 1.0000 0.7273 4 134 1.0000 1.0000 1.0000 2 138 0.9091 0.7692 0.8333 13 147 1.0000 0.5789 0.7333 19 149 0.6667 1.0000 0.8000 2 150 0.6667 1.0000 0.8000 2 21 0.5698 0.5552 0.5624 1940 24 0.5665 0.5503 0.5583 1501 30 0.6101 0.5757 0.5924 905 19 0.5310 0.5163 0.5236 2142 16 0.5312 0.5369 0.5340 2917 38 0.6839 0.6005 0.6395 418 33 0.6255 0.5951 0.6100 741 41 0.6913 0.6341 0.6614 399 0 0.4083 0.0926 0.1510 529 31 0.5924 0.5625 0.5771 752 48 0.6432 0.6010 0.6214 198 50 0.7320 0.6222 0.6727 180 52 0.6685 0.6538 0.6611 182 54 0.7024 0.6705 0.6860 176 68 0.7791 0.6262 0.6943 107 79 0.9020 0.8214 0.8598 56 46 0.8037 0.6187 0.6992 278 56 0.7721 0.7095 0.7394 148 98 0.8000 0.5926 0.6809 27 45 0.6513 0.6804 0.6655 291 73 0.8261 0.7451 0.7835 51 105 0.8571 0.7500 0.8000 8 108 0.9091 0.8333 0.8696 12 110 0.8462 0.7857 0.8148 14 114 0.7778 0.4375 0.5600 16 123 0.7500 0.5000 0.6000 6 135 1.0000 0.5625 0.7200 16 139 0.0000 0.0000 0.0000 1 142 1.0000 0.7500 0.8571 4 146 1.0000 1.0000 1.0000 3 151 1.0000 0.5000 0.6667 2 76 0.8400 0.7000 0.7636 30 58 0.6838 0.7207 0.7018 111 69 0.6824 0.7838 0.7296 74 74 0.8605 0.8043 0.8315 46 71 0.8077 0.7778 0.7925 81 109 0.8889 0.7273 0.8000 11 99 0.8889 0.6667 0.7619 12 117 1.0000 0.1429 0.2500 7 116 0.6000 0.6667 0.6316 9 113 0.5833 0.2917 0.3889 24 121 0.7500 0.5000 0.6000 6 131 0.8333 1.0000 0.9091 5 137 1.0000 0.7500 0.8571 4 81 0.9375 0.6522 0.7692 46 118 0.5000 0.5000 0.5000 6 111 0.6000 0.6000 0.6000 5 102 1.0000 0.7143 0.8333 7 106 1.0000 0.7727 0.8718 22 136 0.7778 0.2800 0.4118 25 140 1.0000 0.5000 0.6667 2 141 0.0000 0.0000 0.0000 5 144 1.0000 0.3000 0.4615 10 152 0.0000 0.0000 0.0000 1 153 0.0000 0.0000 0.0000 1 158 1.0000 0.6250 0.7692 8 156 0.9091 0.4762 0.6250 21 160 1.0000 1.0000 1.0000 2 164 1.0000 1.0000 1.0000 2 143 0.0000 0.0000 0.0000 0 155 0.0000 0.0000 0.0000 0 157 0.5000 0.2500 0.3333 4 161 0.0000 0.0000 0.0000 0 162 1.0000 0.2500 0.4000 12 166 0.0000 0.0000 0.0000 0 175 0.0000 0.0000 0.0000 0 173 0.0000 0.0000 0.0000 0 176 1.0000 1.0000 1.0000 16 177 1.0000 1.0000 1.0000 8 178 1.0000 1.0000 1.0000 4 181 0.0000 0.0000 0.0000 0 182 1.0000 1.0000 1.0000 16 119 1.0000 0.7143 0.8333 21 148 0.0000 0.0000 0.0000 0 154 1.0000 0.7500 0.8571 8 159 1.0000 0.2500 0.4000 4 163 0.0000 0.0000 0.0000 8 167 1.0000 1.0000 1.0000 16 174 1.0000 1.0000 1.0000 8 179 1.0000 1.0000 1.0000 4 183 1.0000 1.0000 1.0000 16 145 0.0000 0.0000 0.0000 0
avg / total 0.5859 0.5847 0.5836 109699