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spacy
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en_core_web_lg

Token Classification
spaCy
English
Eval Results
Model card Files Community
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osanseviero commited on
Commit
9a8869b
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1 Parent(s): fce6aa6

Update spaCy pipeline

Browse files
Files changed (16) hide show
  1. README.md +24 -21
  2. accuracy.json +191 -188
  3. attribute_ruler/patterns +0 -0
  4. config.cfg +29 -31
  5. en_core_web_lg-any-py3-none-any.whl +2 -2
  6. meta.json +194 -191
  7. ner/model +0 -0
  8. parser/model +0 -0
  9. senter/cfg +1 -1
  10. senter/model +0 -0
  11. tagger/cfg +2 -1
  12. tagger/model +0 -0
  13. tok2vec/model +2 -2
  14. tokenizer +0 -0
  15. vocab/strings.json +2 -2
  16. vocab/vectors.cfg +3 -0
README.md CHANGED
@@ -1,7 +1,7 @@
1
  ---
2
  tags:
3
  - spacy
4
- - sentence-similarity
5
  language:
6
  - en
7
  license: mit
@@ -14,47 +14,47 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.8537926165
18
  - name: NER Recall
19
  type: recall
20
- value: 0.8478064904
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.850789024
24
  - task:
25
  name: POS
26
  type: token-classification
27
  metrics:
28
  - name: POS Accuracy
29
  type: accuracy
30
- value: 0.9728657496
31
  - task:
32
  name: SENTER
33
  type: token-classification
34
  metrics:
35
  - name: SENTER Precision
36
  type: precision
37
- value: 0.9029447521
38
  - name: SENTER Recall
39
  type: recall
40
- value: 0.8819183323
41
  - name: SENTER F Score
42
  type: f_score
43
- value: 0.8923076923
44
  - task:
45
  name: UNLABELED_DEPENDENCIES
46
  type: token-classification
47
  metrics:
48
  - name: Unlabeled Dependencies Accuracy
49
  type: accuracy
50
- value: 0.9184566079
51
  - task:
52
  name: LABELED_DEPENDENCIES
53
  type: token-classification
54
  metrics:
55
  - name: Labeled Dependencies Accuracy
56
  type: accuracy
57
- value: 0.9184566079
58
  ---
59
  ### Details: https://spacy.io/models/en#en_core_web_lg
60
 
@@ -63,8 +63,8 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
63
  | Feature | Description |
64
  | --- | --- |
65
  | **Name** | `en_core_web_lg` |
66
- | **Version** | `3.1.0` |
67
- | **spaCy** | `>=3.1.0,<3.2.0` |
68
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
69
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
70
  | **Vectors** | 684830 keys, 684830 unique vectors (300 dimensions) |
@@ -92,12 +92,15 @@ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
92
  | Type | Score |
93
  | --- | --- |
94
  | `TOKEN_ACC` | 99.93 |
95
- | `TAG_ACC` | 97.29 |
96
- | `DEP_UAS` | 91.85 |
97
- | `DEP_LAS` | 90.02 |
98
- | `ENTS_P` | 85.38 |
99
- | `ENTS_R` | 84.78 |
100
- | `ENTS_F` | 85.08 |
101
- | `SENTS_P` | 90.29 |
102
- | `SENTS_R` | 88.19 |
103
- | `SENTS_F` | 89.23 |
 
 
 
 
1
  ---
2
  tags:
3
  - spacy
4
+ - token-classification
5
  language:
6
  - en
7
  license: mit
 
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.8574246409
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.8490084135
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.8531957725
24
  - task:
25
  name: POS
26
  type: token-classification
27
  metrics:
28
  - name: POS Accuracy
29
  type: accuracy
30
+ value: 0.9741780493
31
  - task:
32
  name: SENTER
33
  type: token-classification
34
  metrics:
35
  - name: SENTER Precision
36
  type: precision
37
+ value: 0.9179358172
38
  - name: SENTER Recall
39
  type: recall
40
+ value: 0.8906260307
41
  - name: SENTER F Score
42
  type: f_score
43
+ value: 0.9040747313
44
  - task:
45
  name: UNLABELED_DEPENDENCIES
46
  type: token-classification
47
  metrics:
48
  - name: Unlabeled Dependencies Accuracy
49
  type: accuracy
50
+ value: 0.9200593914
51
  - task:
52
  name: LABELED_DEPENDENCIES
53
  type: token-classification
54
  metrics:
55
  - name: Labeled Dependencies Accuracy
56
  type: accuracy
57
+ value: 0.9200593914
58
  ---
59
  ### Details: https://spacy.io/models/en#en_core_web_lg
60
 
 
63
  | Feature | Description |
64
  | --- | --- |
65
  | **Name** | `en_core_web_lg` |
66
+ | **Version** | `3.2.0` |
67
+ | **spaCy** | `>=3.2.0,<3.3.0` |
68
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
69
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
70
  | **Vectors** | 684830 keys, 684830 unique vectors (300 dimensions) |
 
92
  | Type | Score |
93
  | --- | --- |
94
  | `TOKEN_ACC` | 99.93 |
95
+ | `TOKEN_P` | 99.57 |
96
+ | `TOKEN_R` | 99.58 |
97
+ | `TOKEN_F` | 99.57 |
98
+ | `TAG_ACC` | 97.42 |
99
+ | `SENTS_P` | 91.79 |
100
+ | `SENTS_R` | 89.06 |
101
+ | `SENTS_F` | 90.41 |
102
+ | `DEP_UAS` | 92.01 |
103
+ | `DEP_LAS` | 90.22 |
104
+ | `ENTS_P` | 85.74 |
105
+ | `ENTS_R` | 84.90 |
106
+ | `ENTS_F` | 85.32 |
accuracy.json CHANGED
@@ -1,145 +1,144 @@
1
  {
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  "token_acc": 0.9993053983,
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- "tag_acc": 0.9728657496,
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- "dep_uas": 0.9184566079,
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- "dep_las": 0.9001671544,
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- "ents_p": 0.8537926165,
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- "ents_r": 0.8478064904,
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- "ents_f": 0.850789024,
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- "sents_p": 0.9029447521,
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- "sents_r": 0.8819183323,
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- "sents_f": 0.8923076923,
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- "speed": 9380.6157273927,
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  "dep_las_per_type": {
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  "prep": {
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- "p": 0.8554759314,
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- "r": 0.8651489281,
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- "f": 0.86028524
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  },
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  "det": {
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- "p": 0.9781155758,
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- "r": 0.978594145,
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- "f": 0.9783548019
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  },
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  "pobj": {
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- "f": 0.9647265969
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  },
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  },
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  },
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  "root": {
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- "p": 0.9167794317,
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- "f": 0.9051738535
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- "p": 0.8808435852,
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- "f": 0.8900728112
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  },
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  "amod": {
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@@ -147,64 +146,64 @@
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  "f": 0.8521066208
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  },
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  },
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  "nmod": {
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  },
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  "appos": {
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- "p": 0.6708074534,
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  "predet": {
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  "preconj": {
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  "p": 0.5784313725,
@@ -212,19 +211,19 @@
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  "f": 0.6276595745
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  },
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  "oprd": {
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- "p": 0.8758865248,
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  },
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  "parataxis": {
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  "meta": {
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- "f": 0.5277777778
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  },
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  "csubjpass": {
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  "p": 0.5555555556,
@@ -232,96 +231,100 @@
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  "f": 0.6666666667
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  }
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  },
 
 
 
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  "ents_per_type": {
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  "DATE": {
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- "p": 0.8650594865,
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- "r": 0.8771428571,
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  "GPE": {
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  "ORDINAL": {
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  },
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  "QUANTITY": {
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  "CARDINAL": {
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  },
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  "NORP": {
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- "r": 0.8984,
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- "f": 0.8958915038
 
 
 
 
 
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  },
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  "FAC": {
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  "TIME": {
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- "LOC": {
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- },
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  "LAW": {
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- "PERCENT": {
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  "LANGUAGE": {
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  }
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- }
 
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  }
 
1
  {
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  "token_acc": 0.9993053983,
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+ "token_p": 0.9956742163,
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+ "token_r": 0.9957505887,
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+ "token_f": 0.9957124011,
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+ "tag_acc": 0.9741780493,
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  "dep_las_per_type": {
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  "det": {
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  "advmod": {
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  "xcomp": {
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  "amod": {
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  "compound": {
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  "intj": {
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attribute_ruler/patterns CHANGED
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config.cfg CHANGED
@@ -1,10 +1,8 @@
1
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2
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3
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5
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9
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@@ -24,6 +22,7 @@ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
24
 
25
  [components.attribute_ruler]
26
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27
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28
 
29
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@@ -31,11 +30,13 @@ factory = "lemmatizer"
31
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32
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33
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34
 
35
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36
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37
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38
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39
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40
 
41
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53
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54
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55
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56
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57
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58
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59
 
60
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69
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70
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71
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72
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73
 
74
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87
 
88
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89
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90
 
91
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92
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100
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101
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103
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104
 
105
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111
 
112
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113
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114
 
115
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116
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130
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131
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132
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133
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134
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135
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136
 
137
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145
 
146
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147
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148
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152
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154
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157
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159
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161
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168
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170
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203
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230
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234
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42
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61
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90
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95
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109
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116
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121
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137
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143
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151
 
152
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153
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155
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156
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160
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167
 
168
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194
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196
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