Update spaCy pipeline

.gitattributes

@@ -15,3 +15,8 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
 *.pth filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+*.whl filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*strings.json filter=lfs diff=lfs merge=lfs -text
+vectors filter=lfs diff=lfs merge=lfs -text
+model filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,19 @@
+Copyright 2021 ExplosionAI GmbH
+
+Permission is hereby granted, free of charge, to any person obtaining a copy of
+this software and associated documentation files (the "Software"), to deal in
+the Software without restriction, including without limitation the rights to
+use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies
+of the Software, and to permit persons to whom the Software is furnished to do
+so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSES_SOURCES

@@ -0,0 +1,66 @@
+# OntoNotes 5
+
+* Author: 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
+* URL: https://catalog.ldc.upenn.edu/LDC2013T19
+* License: commercial (licensed by Explosion)
+
+```
+```
+
+
+
+
+# ClearNLP Constituent-to-Dependency Conversion
+
+* Author: Emory University
+* URL: https://github.com/clir/clearnlp-guidelines/blob/master/md/components/dependency_conversion.md
+* License: Citation provided for reference, no code packaged with model
+
+```
+```
+
+
+
+
+# WordNet 3.0
+
+* Author: Princeton University
+* URL: https://wordnet.princeton.edu/
+* License: WordNet 3.0 License
+
+```
+WordNet Release 3.0
+
+This software and database is being provided to you, the LICENSEE, by  
+Princeton University under the following license.  By obtaining, using  
+and/or copying this software and database, you agree that you have  
+read, understood, and will comply with these terms and conditions.:  
+  
+Permission to use, copy, modify and distribute this software and  
+database and its documentation for any purpose and without fee or  
+royalty is hereby granted, provided that you agree to comply with  
+the following copyright notice and statements, including the disclaimer,  
+and that the same appear on ALL copies of the software, database and  
+documentation, including modifications that you make for internal  
+use or for distribution.  
+  
+WordNet 3.0 Copyright 2006 by Princeton University.  All rights reserved.  
+  
+THIS SOFTWARE AND DATABASE IS PROVIDED "AS IS" AND PRINCETON  
+UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR  
+IMPLIED.  BY WAY OF EXAMPLE, BUT NOT LIMITATION, PRINCETON  
+UNIVERSITY MAKES NO REPRESENTATIONS OR WARRANTIES OF MERCHANT-  
+ABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OR THAT THE USE  
+OF THE LICENSED SOFTWARE, DATABASE OR DOCUMENTATION WILL NOT  
+INFRINGE ANY THIRD PARTY PATENTS, COPYRIGHTS, TRADEMARKS OR  
+OTHER RIGHTS.  
+  
+The name of Princeton University or Princeton may not be used in  
+advertising or publicity pertaining to distribution of the software  
+and/or database.  Title to copyright in this software, database and  
+any associated documentation shall at all times remain with  
+Princeton University and LICENSEE agrees to preserve same.```
+
+
+
+

README.md

@@ -0,0 +1,103 @@
+---
+tags:
+- spacy
+- token-classification
+language:
+- en
+license: MIT
+model-index:
+- name: en_core_web_sm
+  results:
+  - task:
+      name: NER
+      type: token-classification
+    metrics:
+    - name: NER Precision
+      type: precision
+      value: 0.8424355924
+    - name: NER Recall
+      type: recall
+      value: 0.8335336538
+    - name: NER F Score
+      type: f_score
+      value: 0.8379609817
+  - task:
+      name: POS
+      type: token-classification
+    metrics:
+    - name: POS Accuracy
+      type: accuracy
+      value: 0.9720712187
+  - task:
+      name: SENTER
+      type: token-classification
+    metrics:
+    - name: SENTER Precision
+      type: precision
+      value: 0.9074955788
+    - name: SENTER Recall
+      type: recall
+      value: 0.8801372122
+    - name: SENTER F Score
+      type: f_score
+      value: 0.893607046
+  - task:
+      name: UNLABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Unlabeled Dependencies Accuracy
+      type: accuracy
+      value: 0.9185392711
+  - task:
+      name: LABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Labeled Dependencies Accuracy
+      type: accuracy
+      value: 0.9185392711
+---
+### Details: https://spacy.io/models/en#en_core_web_sm
+
+English pipeline optimized for CPU. Components: tok2vec, tagger, parser, senter, ner, attribute_ruler, lemmatizer.
+
+| Feature | Description |
+| --- | --- |
+| **Name** | `en_core_web_sm` |
+| **Version** | `3.1.0` |
+| **spaCy** | `>=3.1.0,<3.2.0` |
+| **Default Pipeline** | `tok2vec`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
+| **Components** | `tok2vec`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
+| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
+| **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) |
+| **License** | `MIT` |
+| **Author** | [Explosion](https://explosion.ai) |
+
+### Label Scheme
+
+<details>
+
+<summary>View label scheme (114 labels for 4 components)</summary>
+
+| Component | Labels |
+| --- | --- |
+| **`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`, ```` |
+| **`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` |
+| **`senter`** | `I`, `S` |
+| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
+
+</details>
+
+### Accuracy
+
+| Type | Score |
+| --- | --- |
+| `TOKEN_ACC` | 99.93 |
+| `TAG_ACC` | 97.21 |
+| `DEP_UAS` | 91.85 |
+| `DEP_LAS` | 90.02 |
+| `ENTS_P` | 84.24 |
+| `ENTS_R` | 83.35 |
+| `ENTS_F` | 83.80 |
+| `SENTS_P` | 90.75 |
+| `SENTS_R` | 88.01 |
+| `SENTS_F` | 89.36 |

accuracy.json

@@ -0,0 +1,327 @@
+{
+  "token_acc": 0.9993053983,
+  "tag_acc": 0.9720712187,
+  "dep_uas": 0.9185392711,
+  "dep_las": 0.9001546872,
+  "ents_p": 0.8424355924,
+  "ents_r": 0.8335336538,
+  "ents_f": 0.8379609817,
+  "sents_p": 0.9074955788,
+  "sents_r": 0.8801372122,
+  "sents_f": 0.893607046,
+  "speed": 10426.0619939972,
+  "dep_las_per_type": {
+    "prep": {
+      "p": 0.8554402587,
+      "r": 0.8633276418,
+      "f": 0.8593658527
+    },
+    "det": {
+      "p": 0.9772329247,
+      "r": 0.9783087336,
+      "f": 0.9777705332
+    },
+    "pobj": {
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+      "r": 0.9686628706,
+      "f": 0.9644777228
+    },
+    "nsubj": {
+      "p": 0.9598718747,
+      "r": 0.945279299,
+      "f": 0.9525197007
+    },
+    "aux": {
+      "p": 0.9795737123,
+      "r": 0.9819282471,
+      "f": 0.9807495665
+    },
+    "advmod": {
+      "p": 0.8538267452,
+      "r": 0.8541140838,
+      "f": 0.8539703903
+    },
+    "relcl": {
+      "p": 0.764978602,
+      "r": 0.7783018868,
+      "f": 0.7715827338
+    },
+    "root": {
+      "p": 0.9199754818,
+      "r": 0.8910878026,
+      "f": 0.9053012533
+    },
+    "xcomp": {
+      "p": 0.8813440672,
+      "r": 0.903804738,
+      "f": 0.892433103
+    },
+    "amod": {
+      "p": 0.9171875,
+      "r": 0.9127308066,
+      "f": 0.9149537263
+    },
+    "compound": {
+      "p": 0.916057391,
+      "r": 0.9280463355,
+      "f": 0.9220128918
+    },
+    "poss": {
+      "p": 0.9744672296,
+      "r": 0.9756441224,
+      "f": 0.9750553209
+    },
+    "ccomp": {
+      "p": 0.7747747748,
+      "r": 0.8407331976,
+      "f": 0.8064075015
+    },
+    "attr": {
+      "p": 0.8989490703,
+      "r": 0.9352396972,
+      "f": 0.9167353669
+    },
+    "case": {
+      "p": 0.9801980198,
+      "r": 0.990990991,
+      "f": 0.9855649577
+    },
+    "mark": {
+      "p": 0.9015392781,
+      "r": 0.9001059883,
+      "f": 0.9008220631
+    },
+    "intj": {
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+      "f": 0.6546546547
+    },
+    "advcl": {
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+    },
+    "cc": {
+      "p": 0.8426682692,
+      "r": 0.8385360603,
+      "f": 0.8405970865
+    },
+    "neg": {
+      "p": 0.9461346633,
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+      "f": 0.9489744872
+    },
+    "conj": {
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+    "auxpass": {
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+    "dobj": {
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+    },
+    "nummod": {
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+      "f": 0.9310869014
+    },
+    "npadvmod": {
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+      "r": 0.723268206,
+      "f": 0.7470188956
+    },
+    "prt": {
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+      "r": 0.8915770609,
+      "f": 0.852978997
+    },
+    "pcomp": {
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+      "r": 0.8781512605,
+      "f": 0.8843441467
+    },
+    "expl": {
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+      "r": 0.9914346895,
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+    "acl": {
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+      "r": 0.6988543372,
+      "f": 0.7223005357
+    },
+    "agent": {
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+      "f": 0.9209383145
+    },
+    "dative": {
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+      "r": 0.7224770642,
+      "f": 0.7411764706
+    },
+    "acomp": {
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+    },
+    "dep": {
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+      "f": 0.2362030905
+    },
+    "csubj": {
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+      "f": 0.6347305389
+    },
+    "quantmod": {
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+      "r": 0.7896019496,
+      "f": 0.8244274809
+    },
+    "nmod": {
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+      "r": 0.5807434491,
+      "f": 0.6491825613
+    },
+    "appos": {
+      "p": 0.7011441648,
+      "r": 0.6646420824,
+      "f": 0.6824053452
+    },
+    "predet": {
+      "p": 0.8514056225,
+      "r": 0.9098712446,
+      "f": 0.8796680498
+    },
+    "preconj": {
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+      "r": 0.5930232558,
+      "f": 0.5284974093
+    },
+    "oprd": {
+      "p": 0.8193979933,
+      "r": 0.7313432836,
+      "f": 0.7728706625
+    },
+    "parataxis": {
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+      "r": 0.4989154013,
+      "f": 0.5582524272
+    },
+    "meta": {
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+      "r": 0.3269230769,
+      "f": 0.4594594595
+    },
+    "csubjpass": {
+      "p": 0.5,
+      "r": 0.8333333333,
+      "f": 0.625
+    }
+  },
+  "ents_per_type": {
+    "DATE": {
+      "p": 0.8659955961,
+      "r": 0.873968254,
+      "f": 0.8699636593
+    },
+    "GPE": {
+      "p": 0.9142529395,
+      "r": 0.8892608089,
+      "f": 0.9015837104
+    },
+    "ORG": {
+      "p": 0.789707419,
+      "r": 0.8014316013,
+      "f": 0.7955263158
+    },
+    "FAC": {
+      "p": 0.3679245283,
+      "r": 0.3,
+      "f": 0.3305084746
+    },
+    "CARDINAL": {
+      "p": 0.8146892655,
+      "r": 0.8573127229,
+      "f": 0.8354577057
+    },
+    "PERSON": {
+      "p": 0.8424487259,
+      "r": 0.8847911227,
+      "f": 0.8631009233
+    },
+    "NORP": {
+      "p": 0.9078415521,
+      "r": 0.8984,
+      "f": 0.9030960997
+    },
+    "ORDINAL": {
+      "p": 0.7787114846,
+      "r": 0.8633540373,
+      "f": 0.8188512518
+    },
+    "LOC": {
+      "p": 0.713740458,
+      "r": 0.5955414013,
+      "f": 0.6493055556
+    },
+    "TIME": {
+      "p": 0.712962963,
+      "r": 0.6754385965,
+      "f": 0.6936936937
+    },
+    "PRODUCT": {
+      "p": 0.5510204082,
+      "r": 0.2559241706,
+      "f": 0.3495145631
+    },
+    "QUANTITY": {
+      "p": 0.842519685,
+      "r": 0.5879120879,
+      "f": 0.6925566343
+    },
+    "WORK_OF_ART": {
+      "p": 0.46875,
+      "r": 0.3092783505,
+      "f": 0.3726708075
+    },
+    "EVENT": {
+      "p": 0.595959596,
+      "r": 0.3390804598,
+      "f": 0.4322344322
+    },
+    "MONEY": {
+      "p": 0.9182692308,
+      "r": 0.9020070838,
+      "f": 0.9100655152
+    },
+    "LAW": {
+      "p": 0.5555555556,
+      "r": 0.46875,
+      "f": 0.5084745763
+    },
+    "PERCENT": {
+      "p": 0.92,
+      "r": 0.8805513017,
+      "f": 0.8998435055
+    },
+    "LANGUAGE": {
+      "p": 0.7692307692,
+      "r": 0.625,
+      "f": 0.6896551724
+    }
+  }
+}

config.cfg

@@ -0,0 +1,265 @@
+[paths]
+train = "corpus/en-core-web/train.spacy"
+dev = "corpus/en-core-web/dev.spacy"
+vectors = null
+raw = null
+init_tok2vec = null
+vocab_data = null
+
+[system]
+gpu_allocator = null
+seed = 0
+
+[nlp]
+lang = "en"
+pipeline = ["tok2vec","tagger","parser","senter","attribute_ruler","lemmatizer","ner"]
+disabled = ["senter"]
+before_creation = null
+after_creation = null
+after_pipeline_creation = null
+batch_size = 256
+tokenizer = {"@tokenizers":"spacy.Tokenizer.v1"}
+
+[components]
+
+[components.attribute_ruler]
+factory = "attribute_ruler"
+validate = false
+
+[components.lemmatizer]
+factory = "lemmatizer"
+mode = "rule"
+model = null
+overwrite = false
+
+[components.ner]
+factory = "ner"
+incorrect_spans_key = null
+moves = null
+update_with_oracle_cut_size = 100
+
+[components.ner.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "ner"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = true
+nO = null
+
+[components.ner.model.tok2vec]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.ner.model.tok2vec.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = 96
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,2500,2500,2500]
+include_static_vectors = false
+
+[components.ner.model.tok2vec.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+depth = 4
+window_size = 1
+maxout_pieces = 3
+
+[components.parser]
+factory = "parser"
+learn_tokens = false
+min_action_freq = 30
+moves = null
+update_with_oracle_cut_size = 100
+
+[components.parser.model]
+@architectures = "spacy.TransitionBasedParser.v2"
+state_type = "parser"
+extra_state_tokens = false
+hidden_width = 64
+maxout_pieces = 2
+use_upper = true
+nO = null
+
+[components.parser.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = ${components.tok2vec.model.encode:width}
+upstream = "tok2vec"
+
+[components.senter]
+factory = "senter"
+
+[components.senter.model]
+@architectures = "spacy.Tagger.v1"
+nO = null
+
+[components.senter.model.tok2vec]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.senter.model.tok2vec.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = 16
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [1000,500,500,500]
+include_static_vectors = false
+
+[components.senter.model.tok2vec.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 16
+depth = 2
+window_size = 1
+maxout_pieces = 2
+
+[components.tagger]
+factory = "tagger"
+
+[components.tagger.model]
+@architectures = "spacy.Tagger.v1"
+nO = null
+
+[components.tagger.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = ${components.tok2vec.model.encode:width}
+upstream = "tok2vec"
+
+[components.tok2vec]
+factory = "tok2vec"
+
+[components.tok2vec.model]
+@architectures = "spacy.Tok2Vec.v2"
+
+[components.tok2vec.model.embed]
+@architectures = "spacy.MultiHashEmbed.v2"
+width = ${components.tok2vec.model.encode:width}
+attrs = ["NORM","PREFIX","SUFFIX","SHAPE"]
+rows = [5000,2500,2500,2500]
+include_static_vectors = false
+
+[components.tok2vec.model.encode]
+@architectures = "spacy.MaxoutWindowEncoder.v2"
+width = 96
+depth = 4
+window_size = 1
+maxout_pieces = 3
+
+[corpora]
+
+[corpora.dev]
+@readers = "spacy.Corpus.v1"
+limit = 0
+max_length = 0
+path = ${paths:dev}
+gold_preproc = false
+augmenter = null
+
+[corpora.train]
+@readers = "spacy.Corpus.v1"
+path = ${paths:train}
+max_length = 5000
+gold_preproc = false
+limit = 0
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