Adriane Boyd
commited on
Commit
•
68251ed
1
Parent(s):
f471992
Update spaCy pipeline
Browse files- .gitattributes +2 -0
- README.md +20 -20
- accuracy.json +192 -192
- meta.json +197 -196
- ner/model +1 -1
- ner/moves +1 -1
- parser/model +1 -1
- parser/moves +1 -1
- senter/model +1 -1
- tagger/cfg +2 -1
- tagger/model +2 -2
- tok2vec/model +1 -1
- tokenizer/pkuseg_processors +0 -0
- vocab/key2row +0 -0
- vocab/strings.json +2 -2
- zh_core_web_lg-any-py3-none-any.whl +2 -2
.gitattributes
CHANGED
@@ -19,3 +19,5 @@
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*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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*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
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+
vocab/key2row filter=lfs diff=lfs merge=lfs -text
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README.md
CHANGED
@@ -14,41 +14,41 @@ model-index:
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metrics:
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- name: NER Precision
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type: precision
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-
value: 0.
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- name: NER Recall
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type: recall
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-
value: 0.
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- name: NER F Score
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type: f_score
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-
value: 0.
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- task:
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name: TAG
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type: token-classification
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metrics:
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- name: TAG (XPOS) Accuracy
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type: accuracy
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-
value: 0.
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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-
value: 0.
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Labeled Attachment Score (LAS)
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type: f_score
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-
value: 0.
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- task:
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name: SENTS
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type: token-classification
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metrics:
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- name: Sentences F-Score
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type: f_score
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-
value: 0.
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---
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### Details: https://spacy.io/models/zh#zh_core_web_lg
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@@ -57,8 +57,8 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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| Feature | Description |
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| --- | --- |
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| **Name** | `zh_core_web_lg` |
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-
| **Version** | `3.
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-
| **spaCy** | `>=3.
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| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` |
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| **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` |
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| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
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@@ -70,11 +70,11 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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<details>
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-
<summary>View label scheme (
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| Component | Labels |
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| --- | --- |
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-
| **`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` |
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| **`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` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
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@@ -88,12 +88,12 @@ Chinese pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter,
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| `TOKEN_P` | 94.58 |
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| `TOKEN_R` | 91.36 |
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90 |
| `TOKEN_F` | 92.94 |
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-
| `TAG_ACC` | 90.
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-
| `SENTS_P` |
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93 |
-
| `SENTS_R` | 73.
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94 |
-
| `SENTS_F` | 75.
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95 |
-
| `DEP_UAS` | 70.
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-
| `DEP_LAS` | 65.
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97 |
-
| `ENTS_P` |
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98 |
-
| `ENTS_R` | 69.
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-
| `ENTS_F` | 71.
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metrics:
|
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- name: NER Precision
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type: precision
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+
value: 0.7335270192
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- name: NER Recall
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type: recall
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+
value: 0.6936263736
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- name: NER F Score
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type: f_score
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+
value: 0.7130189212
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- task:
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name: TAG
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type: token-classification
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metrics:
|
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- name: TAG (XPOS) Accuracy
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type: accuracy
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+
value: 0.9027089042
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- task:
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name: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
|
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- name: Unlabeled Attachment Score (UAS)
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type: f_score
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+
value: 0.7072780475
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- task:
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name: LABELED_DEPENDENCIES
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type: token-classification
|
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metrics:
|
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- name: Labeled Attachment Score (LAS)
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type: f_score
|
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+
value: 0.6564620448
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- task:
|
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name: SENTS
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type: token-classification
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metrics:
|
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- name: Sentences F-Score
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type: f_score
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+
value: 0.7530260108
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---
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### Details: https://spacy.io/models/zh#zh_core_web_lg
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| Feature | Description |
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| --- | --- |
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| **Name** | `zh_core_web_lg` |
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+
| **Version** | `3.4.0` |
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+
| **spaCy** | `>=3.4.0,<3.5.0` |
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| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `ner` |
|
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| **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `ner` |
|
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| **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
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<details>
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+
<summary>View label scheme (100 labels for 3 components)</summary>
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| Component | Labels |
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| --- | --- |
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+
| **`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` |
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| **`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` |
|
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
|
80 |
|
|
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| `TOKEN_P` | 94.58 |
|
89 |
| `TOKEN_R` | 91.36 |
|
90 |
| `TOKEN_F` | 92.94 |
|
91 |
+
| `TAG_ACC` | 90.27 |
|
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+
| `SENTS_P` | 77.74 |
|
93 |
+
| `SENTS_R` | 73.01 |
|
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+
| `SENTS_F` | 75.30 |
|
95 |
+
| `DEP_UAS` | 70.73 |
|
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+
| `DEP_LAS` | 65.65 |
|
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+
| `ENTS_P` | 73.35 |
|
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+
| `ENTS_R` | 69.36 |
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+
| `ENTS_F` | 71.30 |
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accuracy.json
CHANGED
@@ -3,207 +3,207 @@
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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.
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"sents_p": 0.
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"sents_r": 0.
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-
"sents_f": 0.
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"dep_uas": 0.
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"dep_las": 0.
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"dep_las_per_type": {
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"dep": {
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"r": 0.
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"f": 0.
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"case": {
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"r": 0.
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"f": 0.
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},
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"nummod": {
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"auxpass": {
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"r": 0.8756756757,
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"nsubj": {
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"acl": {
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"advmod": {
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"mark": {
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"xcomp": {
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"nmod:assmod": {
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"det": {
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"amod": {
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"nmod:prep": {
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"root": {
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"aux:prtmod": {
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"compound:nn": {
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"dobj": {
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"ccomp": {
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"advmod:rcomp": {
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"discourse": {
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"neg": {
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"conj": {
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"cc": {
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"advmod:dvp": {
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"appos": {
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"nmod:poss": {
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"name": {
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"nsubj:xsubj": {
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"p": 0.0,
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"f": 0.0
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"nmod:range": {
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"parataxis:prnmod": {
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"amod:ordmod": {
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"erased": {
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"p": 0.0,
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"f": 0.0
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},
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"etc": {
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"r": 0.9047619048,
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"ents_f": 0.
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"ents_per_type": {
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"DATE": {
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"GPE": {
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"r": 0.
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"f": 0.
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},
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"ORDINAL": {
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"FAC": {
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},
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"ORG": {
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"r": 0.
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"f": 0.
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"LOC": {
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"p": 0.5685618729,
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