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zh_core_web_md

Token Classification
spaCy
Chinese
Eval Results
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adrianeboyd commited on
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caef619
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1 Parent(s): c653306

Update spaCy pipeline

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Files changed (16) hide show
  1. .gitattributes +2 -0
  2. README.md +18 -18
  3. accuracy.json +190 -190
  4. meta.json +195 -194
  5. ner/model +1 -1
  6. ner/moves +1 -1
  7. parser/model +1 -1
  8. parser/moves +1 -1
  9. senter/model +1 -1
  10. tagger/cfg +2 -1
  11. tagger/model +2 -2
  12. tok2vec/model +1 -1
  13. tokenizer/pkuseg_processors +0 -0
  14. vocab/key2row +0 -0
  15. vocab/strings.json +2 -2
  16. zh_core_web_md-any-py3-none-any.whl +2 -2
.gitattributes CHANGED
@@ -19,3 +19,5 @@
19
  *strings.json filter=lfs diff=lfs merge=lfs -text
20
  vectors filter=lfs diff=lfs merge=lfs -text
21
  model filter=lfs diff=lfs merge=lfs -text
 
 
19
  *strings.json filter=lfs diff=lfs merge=lfs -text
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  vectors filter=lfs diff=lfs merge=lfs -text
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  model filter=lfs diff=lfs merge=lfs -text
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+ tokenizer/pkuseg_processors filter=lfs diff=lfs merge=lfs -text
23
+ vocab/key2row filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -14,41 +14,41 @@ model-index:
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
- value: 0.7214151828
18
  - name: NER Recall
19
  type: recall
20
- value: 0.6767032967
21
  - name: NER F Score
22
  type: f_score
23
- value: 0.6983442958
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
- value: 0.8993969506
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
- value: 0.7039979835
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
- value: 0.6522146335
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
- value: 0.7534931861
52
  ---
53
  ### Details: https://spacy.io/models/zh#zh_core_web_md
54
 
@@ -57,8 +57,8 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `zh_core_web_md` |
60
- | **Version** | `3.3.0` |
61
- | **spaCy** | `>=3.3.0.dev0,<3.4.0` |
62
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` |
63
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` |
64
  | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
@@ -70,11 +70,11 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
70
 
71
  <details>
72
 
73
- <summary>View label scheme (99 labels for 3 components)</summary>
74
 
75
  | Component | Labels |
76
  | --- | --- |
77
- | **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X` |
78
  | **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` |
79
  | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
80
 
@@ -88,12 +88,12 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
88
  | `TOKEN_P` | 94.58 |
89
  | `TOKEN_R` | 91.36 |
90
  | `TOKEN_F` | 92.94 |
91
- | `TAG_ACC` | 89.94 |
92
- | `SENTS_P` | 78.18 |
93
- | `SENTS_R` | 72.72 |
94
  | `SENTS_F` | 75.35 |
95
  | `DEP_UAS` | 70.40 |
96
- | `DEP_LAS` | 65.22 |
97
- | `ENTS_P` | 72.14 |
98
- | `ENTS_R` | 67.67 |
99
- | `ENTS_F` | 69.83 |
14
  metrics:
15
  - name: NER Precision
16
  type: precision
17
+ value: 0.7221830158
18
  - name: NER Recall
19
  type: recall
20
+ value: 0.6747252747
21
  - name: NER F Score
22
  type: f_score
23
+ value: 0.6976479945
24
  - task:
25
  name: TAG
26
  type: token-classification
27
  metrics:
28
  - name: TAG (XPOS) Accuracy
29
  type: accuracy
30
+ value: 0.9008590446
31
  - task:
32
  name: UNLABELED_DEPENDENCIES
33
  type: token-classification
34
  metrics:
35
  - name: Unlabeled Attachment Score (UAS)
36
  type: f_score
37
+ value: 0.7039779048
38
  - task:
39
  name: LABELED_DEPENDENCIES
40
  type: token-classification
41
  metrics:
42
  - name: Labeled Attachment Score (LAS)
43
  type: f_score
44
+ value: 0.6517336371
45
  - task:
46
  name: SENTS
47
  type: token-classification
48
  metrics:
49
  - name: Sentences F-Score
50
  type: f_score
51
+ value: 0.7535180869
52
  ---
53
  ### Details: https://spacy.io/models/zh#zh_core_web_md
54
 
57
  | Feature | Description |
58
  | --- | --- |
59
  | **Name** | `zh_core_web_md` |
60
+ | **Version** | `3.4.0` |
61
+ | **spaCy** | `>=3.4.0,<3.5.0` |
62
  | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` |
63
  | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` |
64
  | **Vectors** | 500000 keys, 20000 unique vectors (300 dimensions) |
70
 
71
  <details>
72
 
73
+ <summary>View label scheme (100 labels for 3 components)</summary>
74
 
75
  | Component | Labels |
76
  | --- | --- |
77
+ | **`tagger`** | `AD`, `AS`, `BA`, `CC`, `CD`, `CS`, `DEC`, `DEG`, `DER`, `DEV`, `DT`, `ETC`, `FW`, `IJ`, `INF`, `JJ`, `LB`, `LC`, `M`, `MSP`, `NN`, `NR`, `NT`, `OD`, `ON`, `P`, `PN`, `PU`, `SB`, `SP`, `URL`, `VA`, `VC`, `VE`, `VV`, `X`, `_SP` |
78
  | **`parser`** | `ROOT`, `acl`, `advcl:loc`, `advmod`, `advmod:dvp`, `advmod:loc`, `advmod:rcomp`, `amod`, `amod:ordmod`, `appos`, `aux:asp`, `aux:ba`, `aux:modal`, `aux:prtmod`, `auxpass`, `case`, `cc`, `ccomp`, `compound:nn`, `compound:vc`, `conj`, `cop`, `dep`, `det`, `discourse`, `dobj`, `etc`, `mark`, `mark:clf`, `name`, `neg`, `nmod`, `nmod:assmod`, `nmod:poss`, `nmod:prep`, `nmod:range`, `nmod:tmod`, `nmod:topic`, `nsubj`, `nsubj:xsubj`, `nsubjpass`, `nummod`, `parataxis:prnmod`, `punct`, `xcomp` |
79
  | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
80
 
88
  | `TOKEN_P` | 94.58 |
89
  | `TOKEN_R` | 91.36 |
90
  | `TOKEN_F` | 92.94 |
91
+ | `TAG_ACC` | 90.09 |
92
+ | `SENTS_P` | 78.26 |
93
+ | `SENTS_R` | 72.65 |
94
  | `SENTS_F` | 75.35 |
95
  | `DEP_UAS` | 70.40 |
96
+ | `DEP_LAS` | 65.17 |
97
+ | `ENTS_P` | 72.22 |
98
+ | `ENTS_R` | 67.47 |
99
+ | `ENTS_F` | 69.76 |
accuracy.json CHANGED
@@ -3,167 +3,167 @@
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  "token_p": 0.9458325855,
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  "token_r": 0.9136060443,
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  "token_f": 0.9294400505,
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- "tag_acc": 0.8993969506,
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- "sents_p": 0.7818149275,
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- "sents_r": 0.7271516564,
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- "sents_f": 0.7534931861,
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- "dep_uas": 0.7039979835,
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- "dep_las": 0.6522146335,
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  "dep_las_per_type": {
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  "dep": {
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- "p": 0.479214123,
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- "r": 0.3401030615,
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- "f": 0.3978488269
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  },
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  "case": {
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- "p": 0.81099213,
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- "r": 0.7621241513,
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- "f": 0.7857991124
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  },
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  "nmod:tmod": {
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- "p": 0.7311258278,
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- "r": 0.7510204082,
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- "f": 0.7409395973
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  },
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  "nummod": {
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- "p": 0.8237704918,
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- "r": 0.5356429047,
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- "f": 0.649172386
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  },
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  "mark:clf": {
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- "p": 0.9305724726,
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- "r": 0.5699365908,
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- "f": 0.7069164932
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  },
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  "auxpass": {
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- "p": 0.8548387097,
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- "r": 0.8594594595,
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- "f": 0.8571428571
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  },
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  "nsubj": {
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- "p": 0.7813199842,
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- "r": 0.7285345781,
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- "f": 0.7540045767
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  },
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  "acl": {
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- "p": 0.6691324815,
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- "r": 0.5518580144,
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- "f": 0.6048632219
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  },
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  "advmod": {
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- "p": 0.8206363291,
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- "r": 0.7338472002,
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- "f": 0.7748189815
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  },
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  "mark": {
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- "p": 0.7307514984,
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- "r": 0.69456617,
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- "f": 0.7121995057
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  },
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  "xcomp": {
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- "p": 0.7686703097,
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- "f": 0.7447113091
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  },
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  "det": {
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- "r": 0.6121851201,
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- "f": 0.7087148186
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  },
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  "amod": {
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- "p": 0.7721057429,
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- "r": 0.6653574234,
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  "nmod:prep": {
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- "p": 0.7341652486,
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- "p": 0.9032258065,
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  "compound:nn": {
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- "p": 0.7426056338,
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  "ccomp": {
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  },
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  "advmod:rcomp": {
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- "p": 0.803125,
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  },
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  "nmod:topic": {
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- "p": 0.3718592965,
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  "cop": {
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- "p": 0.7485806975,
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  },
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  "discourse": {
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  },
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  "neg": {
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  "r": 0.6623067776,
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  "aux:modal": {
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  "nmod": {
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  "aux:ba": {
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  },
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  "advmod:loc": {
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  "aux:asp": {
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  },
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  "conj": {
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  },
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  "nsubjpass": {
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  "p": 0.7674418605,
@@ -171,59 +171,59 @@
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  "f": 0.7096774194
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  },
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  "compound:vc": {
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- "p": 0.4943181818,
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  "advcl:loc": {
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- "p": 0.511627907,
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  },
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  "cc": {
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- "p": 0.7040913416,
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  "advmod:dvp": {
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- "p": 0.842519685,
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- "r": 0.6645962733,
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- "f": 0.7430555556
 
 
 
 
 
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  },
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  "appos": {
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- "p": 0.8796992481,
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  "r": 0.8068965517,
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- "f": 0.8417266187
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  },
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  "nmod:poss": {
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- "p": 0.6904761905,
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  },
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  "name": {
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  },
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  "nsubj:xsubj": {
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  "p": 0.0,
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  "f": 0.0
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  },
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- "nmod:range": {
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- "p": 0.7366412214,
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- "r": 0.6476510067,
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- },
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  "parataxis:prnmod": {
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- "r": 0.1278195489,
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  },
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  "amod:ordmod": {
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  "erased": {
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  "p": 0.0,
@@ -231,105 +231,105 @@
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  "f": 0.0
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  },
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  "etc": {
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  }
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  },
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- "ents_p": 0.7214151828,
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- "ents_r": 0.6767032967,
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- "ents_f": 0.6983442958,
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  "ents_per_type": {
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  "DATE": {
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- "p": 0.7714016933,
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  },
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  "GPE": {
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  },
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  "ORDINAL": {
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  },
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  "FAC": {
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  },
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  "ORG": {
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  },
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  "LOC": {
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  },
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  "QUANTITY": {
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- "f": 0.6666666667
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- },
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- "PERSON": {
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- "p": 0.7750841751,
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  },
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  "CARDINAL": {
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  },
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- "TIME": {
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- "f": 0.7493917275
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  },
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  "NORP": {
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- "p": 0.6772151899,
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- "r": 0.4495798319,
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- "f": 0.5404040404
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  },
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  "WORK_OF_ART": {
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- "p": 0.6419753086,
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- "r": 0.3466666667,
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- "f": 0.4502164502
 
 
 
 
 
302
  },
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  "MONEY": {
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- "p": 0.9565217391,
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- "r": 0.8148148148,
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- "f": 0.88
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  },
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  "PERCENT": {
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- "p": 0.8117647059,
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  },
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  "EVENT": {
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- "r": 0.4705882353,
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  },
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  "PRODUCT": {
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- "r": 0.0612244898,
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  },
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  "LAW": {
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- "p": 0.4814814815,
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  "r": 0.2166666667,
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- "f": 0.2988505747
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  },
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  "LANGUAGE": {
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- "f": 0.6086956522
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  }
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  },
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- "speed": 7209.1977233502
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  }
3
  "token_p": 0.9458325855,
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  "token_r": 0.9136060443,
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  "token_f": 0.9294400505,
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+ "tag_acc": 0.9008590446,
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+ "sents_p": 0.7826398852,
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+ "sents_r": 0.7264857666,
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+ "sents_f": 0.7535180869,
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+ "dep_uas": 0.7039779048,
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+ "dep_las": 0.6517336371,
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  "dep_las_per_type": {
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  "dep": {
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