Commit
•
f2f902a
1
Parent(s):
f709d2a
Update spaCy pipeline
Browse files- README.md +16 -16
- accuracy.json +106 -106
- attribute_ruler/patterns +0 -0
- config.cfg +7 -6
- meta.json +109 -109
- mk_core_news_lg-any-py3-none-any.whl +2 -2
- morphologizer/model +2 -2
- ner/model +2 -2
- parser/model +2 -2
- senter/model +1 -1
- tokenizer +1 -1
README.md
CHANGED
@@ -14,20 +14,20 @@ 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: POS
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type: token-classification
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metrics:
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- name: POS (UPOS) 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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@@ -41,14 +41,14 @@ model-index:
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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/mk#mk_core_news_lg
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@@ -57,8 +57,8 @@ Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
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| Feature | Description |
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| --- | --- |
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| **Name** | `mk_core_news_lg` |
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-
| **Version** | `3.
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-
| **spaCy** | `>=3.
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| **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
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| **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
|
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| **Vectors** | 274587 keys, 274587 unique vectors (300 dimensions) |
|
@@ -88,12 +88,12 @@ Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parse
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| `TOKEN_P` | 100.00 |
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| `TOKEN_R` | 100.00 |
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| `TOKEN_F` | 100.00 |
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-
| `SENTS_P` |
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-
| `SENTS_R` |
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-
| `SENTS_F` |
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| `DEP_UAS` | 67.84 |
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-
| `DEP_LAS` | 52.
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-
| `ENTS_P` |
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-
| `ENTS_R` | 75.
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-
| `ENTS_F` | 75.
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-
| `POS_ACC` | 93.
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metrics:
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- name: NER Precision
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type: precision
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+
value: 0.7506382979
|
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- name: NER Recall
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type: recall
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+
value: 0.7506382979
|
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- name: NER F Score
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type: f_score
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+
value: 0.7506382979
|
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- task:
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name: POS
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type: token-classification
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metrics:
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- name: POS (UPOS) Accuracy
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type: accuracy
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+
value: 0.9309414621
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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: Labeled Attachment Score (LAS)
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type: f_score
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+
value: 0.5298142717
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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: 0.6756756757
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---
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### Details: https://spacy.io/models/mk#mk_core_news_lg
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|
|
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| Feature | Description |
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| --- | --- |
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| **Name** | `mk_core_news_lg` |
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+
| **Version** | `3.5.0` |
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61 |
+
| **spaCy** | `>=3.5.0,<3.6.0` |
|
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| **Default Pipeline** | `morphologizer`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
|
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| **Components** | `morphologizer`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
|
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| **Vectors** | 274587 keys, 274587 unique vectors (300 dimensions) |
|
|
|
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| `TOKEN_P` | 100.00 |
|
89 |
| `TOKEN_R` | 100.00 |
|
90 |
| `TOKEN_F` | 100.00 |
|
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+
| `SENTS_P` | 70.42 |
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+
| `SENTS_R` | 64.94 |
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93 |
+
| `SENTS_F` | 67.57 |
|
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| `DEP_UAS` | 67.84 |
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95 |
+
| `DEP_LAS` | 52.98 |
|
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+
| `ENTS_P` | 75.06 |
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+
| `ENTS_R` | 75.06 |
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+
| `ENTS_F` | 75.06 |
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+
| `POS_ACC` | 93.09 |
|
accuracy.json
CHANGED
@@ -3,36 +3,36 @@
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@@ -40,19 +40,19 @@
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@@ -65,9 +65,9 @@
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@@ -80,29 +80,29 @@
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@@ -120,9 +120,9 @@
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@@ -160,101 +160,101 @@
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|
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|
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|
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|
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|
216 |
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|
|
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|
|
|
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|
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|
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|
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|
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|
226 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
251 |
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|
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|
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|
253 |
"LAW": {
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254 |
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|
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|
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|
258 |
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|
259 |
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"pos_acc": 0.9309414621
|
260 |
}
|
attribute_ruler/patterns
CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
|
|
config.cfg
CHANGED
@@ -49,8 +49,8 @@ normalize = false
|
|
49 |
[components.morphologizer.model.tok2vec.embed]
|
50 |
@architectures = "spacy.MultiHashEmbed.v2"
|
51 |
width = ${components.morphologizer.model.tok2vec.encode:width}
|
52 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
53 |
-
rows = [5000,1000,2500,2500,50]
|
54 |
include_static_vectors = true
|
55 |
|
56 |
[components.morphologizer.model.tok2vec.encode]
|
@@ -82,8 +82,8 @@ nO = null
|
|
82 |
[components.ner.model.tok2vec.embed]
|
83 |
@architectures = "spacy.MultiHashEmbed.v2"
|
84 |
width = 96
|
85 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"
|
86 |
-
rows = [5000,1000,2500,2500
|
87 |
include_static_vectors = true
|
88 |
|
89 |
[components.ner.model.tok2vec.encode]
|
@@ -116,8 +116,8 @@ nO = null
|
|
116 |
[components.parser.model.tok2vec.embed]
|
117 |
@architectures = "spacy.MultiHashEmbed.v2"
|
118 |
width = 96
|
119 |
-
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
|
120 |
-
rows = [5000,1000,2500,2500,50]
|
121 |
include_static_vectors = true
|
122 |
|
123 |
[components.parser.model.tok2vec.encode]
|
@@ -186,6 +186,7 @@ eval_frequency = 1000
|
|
186 |
frozen_components = []
|
187 |
before_to_disk = null
|
188 |
annotating_components = []
|
|
|
189 |
|
190 |
[training.batcher]
|
191 |
@batchers = "spacy.batch_by_words.v1"
|
|
|
49 |
[components.morphologizer.model.tok2vec.embed]
|
50 |
@architectures = "spacy.MultiHashEmbed.v2"
|
51 |
width = ${components.morphologizer.model.tok2vec.encode:width}
|
52 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
|
53 |
+
rows = [5000,1000,2500,2500,50,50]
|
54 |
include_static_vectors = true
|
55 |
|
56 |
[components.morphologizer.model.tok2vec.encode]
|
|
|
82 |
[components.ner.model.tok2vec.embed]
|
83 |
@architectures = "spacy.MultiHashEmbed.v2"
|
84 |
width = 96
|
85 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
|
86 |
+
rows = [5000,1000,2500,2500]
|
87 |
include_static_vectors = true
|
88 |
|
89 |
[components.ner.model.tok2vec.encode]
|
|
|
116 |
[components.parser.model.tok2vec.embed]
|
117 |
@architectures = "spacy.MultiHashEmbed.v2"
|
118 |
width = 96
|
119 |
+
attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
|
120 |
+
rows = [5000,1000,2500,2500,50,50]
|
121 |
include_static_vectors = true
|
122 |
|
123 |
[components.parser.model.tok2vec.encode]
|
|
|
186 |
frozen_components = []
|
187 |
before_to_disk = null
|
188 |
annotating_components = []
|
189 |
+
before_update = null
|
190 |
|
191 |
[training.batcher]
|
192 |
@batchers = "spacy.batch_by_words.v1"
|
meta.json
CHANGED
@@ -1,14 +1,14 @@
|
|
1 |
{
|
2 |
"lang":"mk",
|
3 |
"name":"core_news_lg",
|
4 |
-
"version":"3.
|
5 |
"description":"Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.",
|
6 |
"author":"Explosion",
|
7 |
"email":"contact@explosion.ai",
|
8 |
"url":"https://explosion.ai",
|
9 |
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|
10 |
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"spacy_version":">=3.
|
11 |
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|
12 |
"vectors":{
|
13 |
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|
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"vectors":274587,
|
@@ -106,36 +106,36 @@
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|
106 |
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|
107 |
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|
108 |
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|
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|
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|
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|
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|
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|
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|
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121 |
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|
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|
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|
125 |
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|
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133 |
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|
138 |
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|
139 |
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|
140 |
"poss":{
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141 |
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|
@@ -143,19 +143,19 @@
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|
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144 |
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|
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148 |
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|
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|
150 |
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157 |
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|
158 |
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|
159 |
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|
160 |
"pozv":{
|
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|
@@ -168,9 +168,9 @@
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|
168 |
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|
169 |
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|
170 |
"att":{
|
171 |
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|
172 |
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|
173 |
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"f":0.
|
174 |
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|
175 |
"det":{
|
176 |
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|
@@ -183,29 +183,29 @@
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|
183 |
"f":0.0
|
184 |
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|
185 |
"dep":{
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186 |
-
"p":0.
|
187 |
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|
188 |
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"f":0.
|
189 |
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|
190 |
"dobj":{
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191 |
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|
192 |
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"r":0.
|
193 |
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"f":0.
|
194 |
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|
195 |
"ppdo":{
|
196 |
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"p":0.
|
197 |
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"r":0.
|
198 |
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|
199 |
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|
200 |
"neg":{
|
201 |
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|
202 |
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"r":0.
|
203 |
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"f":0.
|
204 |
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205 |
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206 |
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207 |
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"r":0.
|
208 |
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"f":0.
|
209 |
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|
210 |
"mwe":{
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211 |
"p":0.0,
|
@@ -223,9 +223,9 @@
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|
223 |
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224 |
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|
225 |
"advmod":{
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226 |
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|
227 |
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|
228 |
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"f":0.
|
229 |
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|
230 |
"advcl":{
|
231 |
"p":0.0,
|
@@ -263,103 +263,103 @@
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|
263 |
"f":0.0
|
264 |
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|
265 |
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|
266 |
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"speed":
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267 |
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|
268 |
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|
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276 |
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279 |
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|
280 |
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|
281 |
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282 |
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|
283 |
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284 |
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286 |
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287 |
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|
288 |
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289 |
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290 |
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291 |
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292 |
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304 |
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|
305 |
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306 |
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|
307 |
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|
308 |
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"r":
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309 |
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|
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311 |
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312 |
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|
313 |
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314 |
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|
315 |
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316 |
"PERCENT":{
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317 |
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318 |
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|
319 |
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|
320 |
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321 |
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322 |
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|
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|
324 |
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327 |
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329 |
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331 |
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|
334 |
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"f":0.
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|
335 |
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336 |
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|
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344 |
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365 |
{
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|
|
1 |
{
|
2 |
"lang":"mk",
|
3 |
"name":"core_news_lg",
|
4 |
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"version":"3.5.0",
|
5 |
"description":"Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.",
|
6 |
"author":"Explosion",
|
7 |
"email":"contact@explosion.ai",
|
8 |
"url":"https://explosion.ai",
|
9 |
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"spacy_version":">=3.5.0,<3.6.0",
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|
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|
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