adrianeboyd
commited on
Commit
•
138b609
1
Parent(s):
f51487a
Update spaCy pipeline
Browse files- README.md +18 -18
- accuracy.json +108 -108
- attribute_ruler/patterns +0 -0
- config.cfg +7 -6
- meta.json +111 -111
- mk_core_news_md-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
@@ -14,41 +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: 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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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/mk#mk_core_news_md
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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_md` |
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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` |
|
64 |
| **Vectors** | 274587 keys, 20000 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` |
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-
| `DEP_LAS` |
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96 |
-
| `ENTS_P` |
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97 |
-
| `ENTS_R` | 74.
|
98 |
-
| `ENTS_F` | 74.
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99 |
-
| `POS_ACC` |
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metrics:
|
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- name: NER Precision
|
16 |
type: precision
|
17 |
+
value: 0.7472245944
|
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- name: NER Recall
|
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type: recall
|
20 |
+
value: 0.7446808511
|
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- name: NER F Score
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type: f_score
|
23 |
+
value: 0.7459505541
|
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- task:
|
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name: POS
|
26 |
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: 0.9260857837
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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)
|
36 |
type: f_score
|
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+
value: 0.6771344455
|
38 |
- task:
|
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name: LABELED_DEPENDENCIES
|
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type: token-classification
|
41 |
metrics:
|
42 |
- name: Labeled Attachment Score (LAS)
|
43 |
type: f_score
|
44 |
+
value: 0.5201177625
|
45 |
- task:
|
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name: SENTS
|
47 |
type: token-classification
|
48 |
metrics:
|
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- name: Sentences F-Score
|
50 |
type: f_score
|
51 |
+
value: 0.7323943662
|
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---
|
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### Details: https://spacy.io/models/mk#mk_core_news_md
|
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|
|
|
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| Feature | Description |
|
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| --- | --- |
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| **Name** | `mk_core_news_md` |
|
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+
| **Version** | `3.5.0` |
|
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, 20000 unique vectors (300 dimensions) |
|
|
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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` | 80.00 |
|
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+
| `SENTS_R` | 67.53 |
|
93 |
+
| `SENTS_F` | 73.24 |
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+
| `DEP_UAS` | 67.71 |
|
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+
| `DEP_LAS` | 52.01 |
|
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+
| `ENTS_P` | 74.72 |
|
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+
| `ENTS_R` | 74.47 |
|
98 |
+
| `ENTS_F` | 74.60 |
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+
| `POS_ACC` | 92.61 |
|
accuracy.json
CHANGED
@@ -3,36 +3,36 @@
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"token_p": 1.0,
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"token_r": 1.0,
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"token_f": 1.0,
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"sents_r": 0.
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"sents_f": 0.
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"dep_las": 0.
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"dep_las_per_type": {
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"nsubj": {
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"root": {
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"cc": {
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"relcl": {
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"pozm": {
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"poss": {
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"p": 0.0,
|
@@ -40,14 +40,14 @@
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"f": 0.0
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"aux": {
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"prep": {
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"iobj": {
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"p": 0.0,
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@@ -55,9 +55,9 @@
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"f": 0.0
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"pozv": {
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"r": 0.1333333333,
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"quantmod": {
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"p": 0.0,
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@@ -65,9 +65,9 @@
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"f": 0.0
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"att": {
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"det": {
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"p": 0.0,
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@@ -80,19 +80,19 @@
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"f": 0.0
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"dep": {
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"neg": {
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"p": 0.5555555556,
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@@ -100,9 +100,9 @@
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"f": 0.5
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@@ -114,12 +114,12 @@
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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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184 |
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|
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|
186 |
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|
187 |
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|
188 |
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|
189 |
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|
190 |
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|
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|
192 |
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|
193 |
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|
194 |
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|
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|
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|
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|
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209 |
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|
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|
211 |
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|
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|
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|
214 |
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|
215 |
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|
216 |
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|
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|
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|
219 |
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|
220 |
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|
221 |
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|
222 |
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|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
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|
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"WORK_OF_ART": {
|
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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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|
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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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|
253 |
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"PRODUCT": {
|
254 |
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"p": 0.0,
|
255 |
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"r": 0.0,
|
256 |
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|
257 |
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|
258 |
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|
259 |
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"pos_acc": 0.9260857837
|
260 |
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|
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_md",
|
4 |
-
"version":"3.
|
5 |
"description":"Macedonian pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler, lemmatizer.",
|
6 |
"author":"Explosion",
|
7 |
"email":"[email protected]",
|
8 |
"url":"https://explosion.ai",
|
9 |
"license":"CC BY-SA 4.0",
|
10 |
-
"spacy_version":">=3.
|
11 |
-
"spacy_git_version":"
|
12 |
"vectors":{
|
13 |
"width":300,
|
14 |
"vectors":20000,
|
@@ -106,36 +106,36 @@
|
|
106 |
"token_p":1.0,
|
107 |
"token_r":1.0,
|
108 |
"token_f":1.0,
|
109 |
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"sents_p":0.
|
110 |
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"sents_r":0.
|
111 |
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"sents_f":0.
|
112 |
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"dep_uas":0.
|
113 |
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"dep_las":0.
|
114 |
"dep_las_per_type":{
|
115 |
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|
116 |
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|
117 |
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"r":0.
|
118 |
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"f":0.
|
119 |
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|
120 |
"root":{
|
121 |
-
"p":0.
|
122 |
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"r":0.
|
123 |
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"f":0.
|
124 |
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|
125 |
"cc":{
|
126 |
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"p":0.
|
127 |
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"r":0.
|
128 |
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"f":0.
|
129 |
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|
130 |
"relcl":{
|
131 |
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"p":0.
|
132 |
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"r":0.
|
133 |
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"f":0.
|
134 |
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|
135 |
"pozm":{
|
136 |
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"p":0.
|
137 |
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"r":0.
|
138 |
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"f":0.
|
139 |
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|
140 |
"poss":{
|
141 |
"p":0.0,
|
@@ -143,14 +143,14 @@
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|
143 |
"f":0.0
|
144 |
},
|
145 |
"aux":{
|
146 |
-
"p":0.
|
147 |
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"r":0.
|
148 |
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"f":0.
|
149 |
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|
150 |
"prep":{
|
151 |
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"p":0.
|
152 |
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"r":0.
|
153 |
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"f":0.
|
154 |
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|
155 |
"iobj":{
|
156 |
"p":0.0,
|
@@ -158,9 +158,9 @@
|
|
158 |
"f":0.0
|
159 |
},
|
160 |
"pozv":{
|
161 |
-
"p":0.
|
162 |
"r":0.1333333333,
|
163 |
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"f":0.
|
164 |
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|
165 |
"quantmod":{
|
166 |
"p":0.0,
|
@@ -168,9 +168,9 @@
|
|
168 |
"f":0.0
|
169 |
},
|
170 |
"att":{
|
171 |
-
"p":0.
|
172 |
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"r":0.
|
173 |
-
"f":0.
|
174 |
},
|
175 |
"det":{
|
176 |
"p":0.0,
|
@@ -183,19 +183,19 @@
|
|
183 |
"f":0.0
|
184 |
},
|
185 |
"dep":{
|
186 |
-
"p":0.
|
187 |
-
"r":0.
|
188 |
-
"f":0.
|
189 |
},
|
190 |
"dobj":{
|
191 |
-
"p":0.
|
192 |
-
"r":0.
|
193 |
-
"f":0.
|
194 |
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|
195 |
"ppdo":{
|
196 |
-
"p":0.
|
197 |
-
"r":0.
|
198 |
-
"f":0.
|
199 |
},
|
200 |
"neg":{
|
201 |
"p":0.5555555556,
|
@@ -203,9 +203,9 @@
|
|
203 |
"f":0.5
|
204 |
},
|
205 |
"pobj":{
|
206 |
-
"p":0.
|
207 |
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"r":0.
|
208 |
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"f":0.
|
209 |
},
|
210 |
"mwe":{
|
211 |
"p":0.0,
|
@@ -217,12 +217,12 @@
|
|
217 |
"r":0.0,
|
218 |
"f":0.0
|
219 |
},
|
220 |
-
"appos":{
|
221 |
-
"p":0.0,
|
222 |
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"r":0.0,
|
223 |
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"f":0.0
|
224 |
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},
|
225 |
"advmod":{
|
|
|
|
|
|
|
|
|
|
|
226 |
"p":0.0,
|
227 |
"r":0.0,
|
228 |
"f":0.0
|
@@ -263,103 +263,103 @@
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|
263 |
"f":0.0
|
264 |
}
|
265 |
},
|
266 |
-
"speed":
|
267 |
-
"ents_p":0.
|
268 |
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"ents_r":0.
|
269 |
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"ents_f":0.
|
270 |
"ents_per_type":{
|
271 |
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"LOC":{
|
272 |
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"p":0.6666666667,
|
273 |
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"r":0.5747126437,
|
274 |
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"f":0.6172839506
|
275 |
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},
|
276 |
"GPE":{
|
277 |
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"p":0.
|
278 |
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"r":0.
|
279 |
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"f":0.
|
|
|
|
|
|
|
|
|
|
|
280 |
},
|
281 |
"QUANTITY":{
|
282 |
-
"p":0.
|
283 |
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"r":0.
|
284 |
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"f":0.
|
285 |
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|
286 |
"CARDINAL":{
|
287 |
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"p":0.
|
288 |
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"r":0.
|
289 |
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"f":0.
|
290 |
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|
291 |
"DATE":{
|
292 |
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"p":0.
|
293 |
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"r":0.
|
294 |
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"f":0.
|
295 |
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|
296 |
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"
|
297 |
-
"p":0.
|
298 |
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"r":0.
|
299 |
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"f":0.
|
|
|
|
|
|
|
|
|
|
|
300 |
},
|
301 |
"NORP":{
|
302 |
-
"p":0.
|
303 |
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"r":0.
|
304 |
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"f":0.
|
305 |
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|
306 |
"MONEY":{
|
307 |
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"p":0
|
308 |
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"r":0
|
309 |
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"f":0
|
310 |
},
|
311 |
"ORDINAL":{
|
312 |
"p":0.5,
|
313 |
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"r":0.
|
314 |
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"f":0.
|
315 |
},
|
316 |
"PERCENT":{
|
317 |
"p":1.0,
|
318 |
"r":1.0,
|
319 |
"f":1.0
|
320 |
},
|
321 |
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"PERSON":{
|
322 |
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"p":0.7843137255,
|
323 |
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"r":0.8,
|
324 |
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"f":0.7920792079
|
325 |
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},
|
326 |
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"FAC":{
|
327 |
-
"p":0.3,
|
328 |
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"r":0.15,
|
329 |
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"f":0.2
|
330 |
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},
|
331 |
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"ORG":{
|
332 |
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"p":0.5454545455,
|
333 |
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"r":0.7346938776,
|
334 |
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"f":0.6260869565
|
335 |
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},
|
336 |
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"EVENT":{
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337 |
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|
338 |
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"r":0.4705882353,
|
339 |
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|
340 |
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|
341 |
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|
342 |
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|
343 |
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|
344 |
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"f":0.
|
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|
346 |
"LANGUAGE":{
|
347 |
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|
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|
349 |
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|
350 |
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|
|
|
|
|
|
|
|
|
|
|
351 |
"TIME":{
|
352 |
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|
353 |
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"r":0.
|
354 |
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|
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|
|
|
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|
355 |
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|
356 |
"LAW":{
|
357 |
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|
358 |
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|
359 |
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|
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|
360 |
}
|
361 |
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|
362 |
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"pos_acc":0.
|
363 |
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|
364 |
"sources":[
|
365 |
{
|
|
|
1 |
{
|
2 |
"lang":"mk",
|
3 |
"name":"core_news_md",
|
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":"[email protected]",
|
8 |
"url":"https://explosion.ai",
|
9 |
"license":"CC BY-SA 4.0",
|
10 |
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"spacy_version":">=3.5.0,<3.6.0",
|
11 |
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"spacy_git_version":"9e0322de1",
|
12 |
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|
13 |
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|
14 |
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|
|
|
106 |
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|
107 |
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|
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|
109 |
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"sents_p":0.8,
|
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|
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|
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|
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|
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|
117 |
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|
118 |
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|
119 |
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|
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|
121 |
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|
122 |
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|
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|
124 |
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|
125 |
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|
126 |
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|
127 |
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|
128 |
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130 |
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|
131 |
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|
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|
133 |
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|
134 |
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135 |
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|
137 |
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|
138 |
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|
139 |
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|
140 |
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|
141 |
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|
|
|
143 |
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|
144 |
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|
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|
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|
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|
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|
153 |
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|
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|
|
|
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|
159 |
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|
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|
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"p":0.2,
|
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|
163 |
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"f":0.16
|
164 |
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|
165 |
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|
166 |
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|
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