NimmyhBas commited on
Commit
7d6af26
1 Parent(s): 4c7879b

Update spaCy pipeline

Browse files
.gitattributes CHANGED
@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ en_core_web_sm-any-py3-none-any.whl filter=lfs diff=lfs merge=lfs -text
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+ ner/model filter=lfs diff=lfs merge=lfs -text
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+ tok2vec/model filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,97 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - spacy
4
+ - token-classification
5
+ language:
6
+ - en
7
+ license: mit
8
+ model-index:
9
+ - name: en_core_web_sm
10
+ results:
11
+ - task:
12
+ name: NER
13
+ type: token-classification
14
+ metrics:
15
+ - name: NER Precision
16
+ type: precision
17
+ value: 0.8454836771
18
+ - name: NER Recall
19
+ type: recall
20
+ value: 0.8456530449
21
+ - name: NER F Score
22
+ type: f_score
23
+ value: 0.8455683525
24
+ - task:
25
+ name: TAG
26
+ type: token-classification
27
+ metrics:
28
+ - name: TAG (XPOS) Accuracy
29
+ type: accuracy
30
+ value: 0.97246532
31
+ - task:
32
+ name: UNLABELED_DEPENDENCIES
33
+ type: token-classification
34
+ metrics:
35
+ - name: Unlabeled Attachment Score (UAS)
36
+ type: f_score
37
+ value: 0.9175304332
38
+ - task:
39
+ name: LABELED_DEPENDENCIES
40
+ type: token-classification
41
+ metrics:
42
+ - name: Labeled Attachment Score (LAS)
43
+ type: f_score
44
+ value: 0.89874821
45
+ - task:
46
+ name: SENTS
47
+ type: token-classification
48
+ metrics:
49
+ - name: Sentences F-Score
50
+ type: f_score
51
+ value: 0.9059485531
52
+ ---
53
+ English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.
54
+
55
+ | Feature | Description |
56
+ | --- | --- |
57
+ | **Name** | `en_core_web_sm` |
58
+ | **Version** | `3.7.1` |
59
+ | **spaCy** | `>=3.7.2,<3.8.0` |
60
+ | **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
61
+ | **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
62
+ | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
63
+ | **Sources** | [OntoNotes 5](https://catalog.ldc.upenn.edu/LDC2013T19) (Ralph Weischedel, Martha Palmer, Mitchell Marcus, Eduard Hovy, Sameer Pradhan, Lance Ramshaw, Nianwen Xue, Ann Taylor, Jeff Kaufman, Michelle Franchini, Mohammed El-Bachouti, Robert Belvin, Ann Houston)<br>[ClearNLP Constituent-to-Dependency Conversion](https://github.com/clir/clearnlp-guidelines/blob/master/md/components/dependency_conversion.md) (Emory University)<br>[WordNet 3.0](https://wordnet.princeton.edu/) (Princeton University) |
64
+ | **License** | `MIT` |
65
+ | **Author** | [Explosion](https://explosion.ai) |
66
+
67
+ ### Label Scheme
68
+
69
+ <details>
70
+
71
+ <summary>View label scheme (113 labels for 3 components)</summary>
72
+
73
+ | Component | Labels |
74
+ | --- | --- |
75
+ | **`tagger`** | `$`, `''`, `,`, `-LRB-`, `-RRB-`, `.`, `:`, `ADD`, `AFX`, `CC`, `CD`, `DT`, `EX`, `FW`, `HYPH`, `IN`, `JJ`, `JJR`, `JJS`, `LS`, `MD`, `NFP`, `NN`, `NNP`, `NNPS`, `NNS`, `PDT`, `POS`, `PRP`, `PRP$`, `RB`, `RBR`, `RBS`, `RP`, `SYM`, `TO`, `UH`, `VB`, `VBD`, `VBG`, `VBN`, `VBP`, `VBZ`, `WDT`, `WP`, `WP$`, `WRB`, `XX`, `_SP`, ```` |
76
+ | **`parser`** | `ROOT`, `acl`, `acomp`, `advcl`, `advmod`, `agent`, `amod`, `appos`, `attr`, `aux`, `auxpass`, `case`, `cc`, `ccomp`, `compound`, `conj`, `csubj`, `csubjpass`, `dative`, `dep`, `det`, `dobj`, `expl`, `intj`, `mark`, `meta`, `neg`, `nmod`, `npadvmod`, `nsubj`, `nsubjpass`, `nummod`, `oprd`, `parataxis`, `pcomp`, `pobj`, `poss`, `preconj`, `predet`, `prep`, `prt`, `punct`, `quantmod`, `relcl`, `xcomp` |
77
+ | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
78
+
79
+ </details>
80
+
81
+ ### Accuracy
82
+
83
+ | Type | Score |
84
+ | --- | --- |
85
+ | `TOKEN_ACC` | 99.86 |
86
+ | `TOKEN_P` | 99.57 |
87
+ | `TOKEN_R` | 99.58 |
88
+ | `TOKEN_F` | 99.57 |
89
+ | `TAG_ACC` | 97.25 |
90
+ | `SENTS_P` | 92.02 |
91
+ | `SENTS_R` | 89.21 |
92
+ | `SENTS_F` | 90.59 |
93
+ | `DEP_UAS` | 91.75 |
94
+ | `DEP_LAS` | 89.87 |
95
+ | `ENTS_P` | 84.55 |
96
+ | `ENTS_R` | 84.57 |
97
+ | `ENTS_F` | 84.56 |
attribute_ruler/patterns ADDED
Binary file (14.7 kB). View file
 
config.cfg ADDED
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1
+ [paths]
2
+ train = null
3
+ dev = null
4
+ vectors = null
5
+ init_tok2vec = null
6
+
7
+ [system]
8
+ gpu_allocator = null
9
+ seed = 0
10
+
11
+ [nlp]
12
+ lang = "en"
13
+ pipeline = ["tok2vec","tagger","parser","senter","attribute_ruler","lemmatizer","ner"]
14
+ disabled = ["senter"]
15
+ before_creation = null
16
+ after_creation = null
17
+ after_pipeline_creation = null
18
+ batch_size = 256
19
+ tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
20
+ vectors = {"@vectors":"spacy.Vectors.v1"}
21
+
22
+ [components]
23
+
24
+ [components.attribute_ruler]
25
+ factory = "attribute_ruler"
26
+ scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
27
+ validate = false
28
+
29
+ [components.lemmatizer]
30
+ factory = "lemmatizer"
31
+ mode = "rule"
32
+ model = null
33
+ overwrite = false
34
+ scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
35
+
36
+ [components.ner]
37
+ factory = "ner"
38
+ incorrect_spans_key = null
39
+ moves = null
40
+ scorer = {"@scorers":"spacy.ner_scorer.v1"}
41
+ update_with_oracle_cut_size = 100
42
+
43
+ [components.ner.model]
44
+ @architectures = "spacy.TransitionBasedParser.v2"
45
+ state_type = "ner"
46
+ extra_state_tokens = false
47
+ hidden_width = 64
48
+ maxout_pieces = 2
49
+ use_upper = true
50
+ nO = null
51
+
52
+ [components.ner.model.tok2vec]
53
+ @architectures = "spacy.Tok2Vec.v2"
54
+
55
+ [components.ner.model.tok2vec.embed]
56
+ @architectures = "spacy.MultiHashEmbed.v2"
57
+ width = 96
58
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
59
+ rows = [5000,1000,2500,2500]
60
+ include_static_vectors = false
61
+
62
+ [components.ner.model.tok2vec.encode]
63
+ @architectures = "spacy.MaxoutWindowEncoder.v2"
64
+ width = 96
65
+ depth = 4
66
+ window_size = 1
67
+ maxout_pieces = 3
68
+
69
+ [components.parser]
70
+ factory = "parser"
71
+ learn_tokens = false
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+ min_action_freq = 30
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+ moves = null
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+ scorer = {"@scorers":"spacy.parser_scorer.v1"}
75
+ update_with_oracle_cut_size = 100
76
+
77
+ [components.parser.model]
78
+ @architectures = "spacy.TransitionBasedParser.v2"
79
+ state_type = "parser"
80
+ extra_state_tokens = false
81
+ hidden_width = 64
82
+ maxout_pieces = 2
83
+ use_upper = true
84
+ nO = null
85
+
86
+ [components.parser.model.tok2vec]
87
+ @architectures = "spacy.Tok2VecListener.v1"
88
+ width = ${components.tok2vec.model.encode:width}
89
+ upstream = "tok2vec"
90
+
91
+ [components.senter]
92
+ factory = "senter"
93
+ overwrite = false
94
+ scorer = {"@scorers":"spacy.senter_scorer.v1"}
95
+
96
+ [components.senter.model]
97
+ @architectures = "spacy.Tagger.v2"
98
+ nO = null
99
+ normalize = false
100
+
101
+ [components.senter.model.tok2vec]
102
+ @architectures = "spacy.Tok2Vec.v2"
103
+
104
+ [components.senter.model.tok2vec.embed]
105
+ @architectures = "spacy.MultiHashEmbed.v2"
106
+ width = 16
107
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
108
+ rows = [1000,500,500,500,50]
109
+ include_static_vectors = false
110
+
111
+ [components.senter.model.tok2vec.encode]
112
+ @architectures = "spacy.MaxoutWindowEncoder.v2"
113
+ width = 16
114
+ depth = 2
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+ window_size = 1
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+ maxout_pieces = 2
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+
118
+ [components.tagger]
119
+ factory = "tagger"
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+ label_smoothing = 0.0
121
+ neg_prefix = "!"
122
+ overwrite = false
123
+ scorer = {"@scorers":"spacy.tagger_scorer.v1"}
124
+
125
+ [components.tagger.model]
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+ @architectures = "spacy.Tagger.v2"
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+ nO = null
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+ normalize = false
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+
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+ [components.tagger.model.tok2vec]
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+ @architectures = "spacy.Tok2VecListener.v1"
132
+ width = ${components.tok2vec.model.encode:width}
133
+ upstream = "tok2vec"
134
+
135
+ [components.tok2vec]
136
+ factory = "tok2vec"
137
+
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+ [components.tok2vec.model]
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+ @architectures = "spacy.Tok2Vec.v2"
140
+
141
+ [components.tok2vec.model.embed]
142
+ @architectures = "spacy.MultiHashEmbed.v2"
143
+ width = ${components.tok2vec.model.encode:width}
144
+ attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY","IS_SPACE"]
145
+ rows = [5000,1000,2500,2500,50,50]
146
+ include_static_vectors = false
147
+
148
+ [components.tok2vec.model.encode]
149
+ @architectures = "spacy.MaxoutWindowEncoder.v2"
150
+ width = 96
151
+ depth = 4
152
+ window_size = 1
153
+ maxout_pieces = 3
154
+
155
+ [corpora]
156
+
157
+ [corpora.dev]
158
+ @readers = "spacy.Corpus.v1"
159
+ path = ${paths.dev}
160
+ gold_preproc = false
161
+ max_length = 0
162
+ limit = 0
163
+ augmenter = null
164
+
165
+ [corpora.train]
166
+ @readers = "spacy.Corpus.v1"
167
+ path = ${paths.train}
168
+ gold_preproc = false
169
+ max_length = 0
170
+ limit = 0
171
+ augmenter = null
172
+
173
+ [training]
174
+ train_corpus = "corpora.train"
175
+ dev_corpus = "corpora.dev"
176
+ seed = ${system:seed}
177
+ gpu_allocator = ${system:gpu_allocator}
178
+ dropout = 0.1
179
+ accumulate_gradient = 1
180
+ patience = 5000
181
+ max_epochs = 0
182
+ max_steps = 100000
183
+ eval_frequency = 1000
184
+ frozen_components = []
185
+ before_to_disk = null
186
+ annotating_components = []
187
+ before_update = null
188
+
189
+ [training.batcher]
190
+ @batchers = "spacy.batch_by_words.v1"
191
+ discard_oversize = false
192
+ tolerance = 0.2
193
+ get_length = null
194
+
195
+ [training.batcher.size]
196
+ @schedules = "compounding.v1"
197
+ start = 100
198
+ stop = 1000
199
+ compound = 1.001
200
+ t = 0.0
201
+
202
+ [training.logger]
203
+ @loggers = "spacy.ConsoleLogger.v1"
204
+ progress_bar = false
205
+
206
+ [training.optimizer]
207
+ @optimizers = "Adam.v1"
208
+ beta1 = 0.9
209
+ beta2 = 0.999
210
+ L2_is_weight_decay = true
211
+ L2 = 0.01
212
+ grad_clip = 1.0
213
+ use_averages = true
214
+ eps = 0.00000001
215
+ learn_rate = 0.001
216
+
217
+ [training.score_weights]
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+ tag_acc = 0.16
219
+ dep_uas = 0.0
220
+ dep_las = 0.16
221
+ dep_las_per_type = null
222
+ sents_p = null
223
+ sents_r = null
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+ sents_f = 0.02
225
+ lemma_acc = 0.5
226
+ ents_f = 0.16
227
+ ents_p = 0.0
228
+ ents_r = 0.0
229
+ ents_per_type = null
230
+ speed = 0.0
231
+
232
+ [pretraining]
233
+
234
+ [initialize]
235
+ vocab_data = null
236
+ vectors = ${paths.vectors}
237
+ init_tok2vec = ${paths.init_tok2vec}
238
+ before_init = null
239
+ after_init = null
240
+
241
+ [initialize.components]
242
+
243
+ [initialize.components.ner]
244
+
245
+ [initialize.components.ner.labels]
246
+ @readers = "spacy.read_labels.v1"
247
+ path = "corpus/labels/ner.json"
248
+ require = false
249
+
250
+ [initialize.components.parser]
251
+
252
+ [initialize.components.parser.labels]
253
+ @readers = "spacy.read_labels.v1"
254
+ path = "corpus/labels/parser.json"
255
+ require = false
256
+
257
+ [initialize.components.tagger]
258
+
259
+ [initialize.components.tagger.labels]
260
+ @readers = "spacy.read_labels.v1"
261
+ path = "corpus/labels/tagger.json"
262
+ require = false
263
+
264
+ [initialize.lookups]
265
+ @misc = "spacy.LookupsDataLoader.v1"
266
+ lang = ${nlp.lang}
267
+ tables = ["lexeme_norm"]
268
+
269
+ [initialize.tokenizer]
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+ {
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+ "lang":"en",
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+ "name":"core_web_sm",
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+ "version":"3.7.1",
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+ "description":"English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.",
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+ "author":"Explosion",
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+ "email":"contact@explosion.ai",
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+ "url":"https://explosion.ai",
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+ "license":"MIT",
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+ "spacy_version":">=3.7.2,<3.8.0",
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+ "spacy_git_version":"bd2c17e20",
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+ "vectors":{
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+ "width":0,
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+ },
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+ "labels":{
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+ "tok2vec":[
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+
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+ ],
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+ "tagger":[
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+ "$",
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+ "''",
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+ ",",
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+ "-LRB-",
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+ "-RRB-",
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+ ".",
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+ ":",
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+ "ADD",
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+ "AFX",
32
+ "CC",
33
+ "CD",
34
+ "DT",
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+ "EX",
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+ "FW",
37
+ "HYPH",
38
+ "IN",
39
+ "JJ",
40
+ "JJR",
41
+ "JJS",
42
+ "LS",
43
+ "MD",
44
+ "NFP",
45
+ "NN",
46
+ "NNP",
47
+ "NNPS",
48
+ "NNS",
49
+ "PDT",
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+ "POS",
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+ "PRP",
52
+ "PRP$",
53
+ "RB",
54
+ "RBR",
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+ "RBS",
56
+ "RP",
57
+ "SYM",
58
+ "TO",
59
+ "UH",
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+ "VB",
61
+ "VBD",
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+ "VBG",
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+ "VBN",
64
+ "VBP",
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+ "VBZ",
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+ "WDT",
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+ "WP",
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+ "WP$",
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+ "WRB",
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+ "XX",
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+ "_SP",
72
+ "``"
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+ ],
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+ "parser":[
75
+ "ROOT",
76
+ "acl",
77
+ "acomp",
78
+ "advcl",
79
+ "advmod",
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+ "agent",
81
+ "amod",
82
+ "appos",
83
+ "attr",
84
+ "aux",
85
+ "auxpass",
86
+ "case",
87
+ "cc",
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+ "ccomp",
89
+ "compound",
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+ "conj",
91
+ "csubj",
92
+ "csubjpass",
93
+ "dative",
94
+ "dep",
95
+ "det",
96
+ "dobj",
97
+ "expl",
98
+ "intj",
99
+ "mark",
100
+ "meta",
101
+ "neg",
102
+ "nmod",
103
+ "npadvmod",
104
+ "nsubj",
105
+ "nsubjpass",
106
+ "nummod",
107
+ "oprd",
108
+ "parataxis",
109
+ "pcomp",
110
+ "pobj",
111
+ "poss",
112
+ "preconj",
113
+ "predet",
114
+ "prep",
115
+ "prt",
116
+ "punct",
117
+ "quantmod",
118
+ "relcl",
119
+ "xcomp"
120
+ ],
121
+ "attribute_ruler":[
122
+
123
+ ],
124
+ "lemmatizer":[
125
+
126
+ ],
127
+ "ner":[
128
+ "CARDINAL",
129
+ "DATE",
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