EC2 Default User commited on May 2, 2022

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1 Parent(s): b53d61c

Update spaCy pipeline

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LICENSES_SOURCES +0 -31
README.md +58 -44
accuracy.json +268 -268
attribute_ruler/patterns +0 -0
config.cfg +39 -17
lemmatizer/cfg +1198 -0
lemmatizer/{lookups/lookups.bin → model} +2 -2
lemmatizer/trees +0 -0
meta.json +274 -287
morphologizer/model +2 -2
ner/model +2 -2
nl_core_news_lg-any-py3-none-any.whl +2 -2
parser/model +1 -1
parser/moves +1 -1
senter/model +2 -2
tagger/cfg +1 -0
tagger/model +2 -2
tok2vec/model +2 -2
tokenizer +0 -0
vocab/strings.json +2 -2

LICENSES_SOURCES CHANGED Viewed

@@ -1758,37 +1758,6 @@ Creative Commons may be contacted at creativecommons.org.
-# spaCy lookups data
-* Author: Explosion
-* URL: https://github.com/explosion/spacy-lookups-data
-* License: MIT
-```
-Copyright 2019-2021 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.
-```
 # Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)
 * Author: Explosion


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1761	# Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)
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1763	* Author: Explosion

README.md CHANGED Viewed

@@ -14,61 +14,76 @@ model-index:
     metrics:
     - name: NER Precision
       type: precision
-      value: 0.7772241993
     - name: NER Recall
       type: recall
-      value: 0.755186722
     - name: NER F Score
       type: f_score
-      value: 0.7660470011
   - task:
       name: POS
       type: token-classification
     metrics:
-    - name: POS Accuracy
       type: accuracy
-      value: 0.9543293348
   - task:
-      name: SENTER
       type: token-classification
     metrics:
-    - name: SENTER Precision
-      type: precision
-      value: 0.866340098
-    - name: SENTER Recall
-      type: recall
-      value: 0.8880918221
-    - name: SENTER F Score
-      type: f_score
-      value: 0.8770811194
   - task:
-      name: UNLABELED_DEPENDENCIES
       type: token-classification
     metrics:
-    - name: Unlabeled Dependencies Accuracy
       type: accuracy
-      value: 0.8701736595
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
-    - name: Labeled Dependencies Accuracy
-      type: accuracy
-      value: 0.8701736595
 ---
 ### Details: https://spacy.io/models/nl#nl_core_news_lg
-Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, parser, senter, ner, attribute_ruler, lemmatizer.
 | Feature | Description |
 | --- | --- |
 | **Name** | `nl_core_news_lg` |
-| **Version** | `3.2.0` |
-| **spaCy** | `>=3.2.0,<3.3.0` |
-| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `attribute_ruler`, `lemmatizer`, `ner` |
-| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `senter`, `attribute_ruler`, `lemmatizer`, `ner` |
 | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
-| **Sources** | [UD Dutch LassySmall v2.8](https://github.com/UniversalDependencies/UD_Dutch-LassySmall) (Bouma, Gosse; van Noord, Gertjan)<br />[Dutch NER Annotations for UD LassySmall](https://nlp.town) (NLP Town)<br />[UD Dutch LassySmall v2.8](https://github.com/UniversalDependencies/UD_Dutch-LassySmall) (Bouma, Gosse; van Noord, Gertjan)<br />[UD Dutch Alpino v2.8](https://github.com/UniversalDependencies/UD_Dutch-Alpino) (Zeman, Daniel; Žabokrtský, Zdeněk; Bouma, Gosse; van Noord, Gertjan)<br />[spaCy lookups data](https://github.com/explosion/spacy-lookups-data) (Explosion)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) |
 | **License** | `CC BY-SA 4.0` |
 | **Author** | [Explosion](https://explosion.ai) |
@@ -76,14 +91,13 @@ Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, pa
 <details>
-<summary>View label scheme (323 labels for 5 components)</summary>
 | Component | Labels |
 | --- | --- |
 | **`morphologizer`** | `POS=PRON\|Person=3\|PronType=Dem`, `Number=Sing\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=ADV`, `POS=VERB\|VerbForm=Part`, `POS=PUNCT`, `Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `POS=ADP`, `POS=NUM`, `Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `POS=SCONJ`, `Definite=Def\|POS=DET`, `Gender=Com\|Number=Sing\|POS=NOUN`, `Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Degree=Pos\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=PROPN`, `Gender=Com\|Number=Sing\|POS=PROPN`, `POS=AUX\|VerbForm=Inf`, `Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `POS=DET`, `Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|Person=3\|PronType=Prs`, `POS=CCONJ`, `Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADJ`, `Case=Nom\|POS=PRON\|Person=1\|PronType=Prs`, `Definite=Ind\|POS=DET`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|PronType=Rel`, `Case=Acc\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Gender=Com,Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PROPN`, `POS=PRON\|PronType=Ind`, `POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|POS=PRON\|PronType=Rcp`, `Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=NOUN`, `POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Abbr=Yes\|POS=X`, `Gender=Com,Neut\|Number=Sing\|POS=PROPN`, `Degree=Sup\|POS=ADJ`, `POS=ADJ`, `Number=Sing\|POS=PROPN`, `POS=PRON\|PronType=Dem`, `POS=AUX\|VerbForm=Part`, `POS=PRON\|Person=3\|PronType=Rel`, `Number=Plur\|POS=PROPN`, `POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PRON\|Person=2\|PronType=Prs`, `POS=INTJ`, `Case=Acc\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=PRON\|PronType=Int`, `POS=PRON\|Person=2\|PronType=Prs`, `POS=PRON\|Person=3`, `Case=Gen\|POS=PRON\|Person=2\|PronType=Prs`, `POS=X` |
 | **`tagger`** | `ADJ\|nom\|basis\|met-e\|mv-n`, `ADJ\|nom\|basis\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|basis\|met-e\|zonder-n\|stan`, `ADJ\|nom\|basis\|zonder\|mv-n`, `ADJ\|nom\|basis\|zonder\|zonder-n`, `ADJ\|nom\|comp\|met-e\|mv-n`, `ADJ\|nom\|comp\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|met-e\|mv-n`, `ADJ\|nom\|sup\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|sup\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|zonder\|zonder-n`, `ADJ\|postnom\|basis\|met-s`, `ADJ\|postnom\|basis\|zonder`, `ADJ\|postnom\|comp\|met-s`, `ADJ\|prenom\|basis\|met-e\|bijz`, `ADJ\|prenom\|basis\|met-e\|stan`, `ADJ\|prenom\|basis\|zonder`, `ADJ\|prenom\|comp\|met-e\|stan`, `ADJ\|prenom\|comp\|zonder`, `ADJ\|prenom\|sup\|met-e\|stan`, `ADJ\|prenom\|sup\|zonder`, `ADJ\|vrij\|basis\|zonder`, `ADJ\|vrij\|comp\|zonder`, `ADJ\|vrij\|dim\|zonder`, `ADJ\|vrij\|sup\|zonder`, `BW`, `LET`, `LID\|bep\|dat\|evmo`, `LID\|bep\|gen\|evmo`, `LID\|bep\|gen\|rest3`, `LID\|bep\|stan\|evon`, `LID\|bep\|stan\|rest`, `LID\|onbep\|stan\|agr`, `N\|eigen\|ev\|basis\|gen`, `N\|eigen\|ev\|basis\|genus\|stan`, `N\|eigen\|ev\|basis\|onz\|stan`, `N\|eigen\|ev\|basis\|zijd\|stan`, `N\|eigen\|ev\|dim\|onz\|stan`, `N\|eigen\|mv\|basis`, `N\|soort\|ev\|basis\|dat`, `N\|soort\|ev\|basis\|gen`, `N\|soort\|ev\|basis\|genus\|stan`, `N\|soort\|ev\|basis\|onz\|stan`, `N\|soort\|ev\|basis\|zijd\|stan`, `N\|soort\|ev\|dim\|onz\|stan`, `N\|soort\|mv\|basis`, `N\|soort\|mv\|dim`, `SPEC\|afgebr`, `SPEC\|afk`, `SPEC\|deeleigen`, `SPEC\|enof`, `SPEC\|meta`, `SPEC\|symb`, `SPEC\|vreemd`, `TSW`, `TW\|hoofd\|nom\|mv-n\|basis`, `TW\|hoofd\|nom\|mv-n\|dim`, `TW\|hoofd\|nom\|zonder-n\|basis`, `TW\|hoofd\|nom\|zonder-n\|dim`, `TW\|hoofd\|prenom\|stan`, `TW\|hoofd\|vrij`, `TW\|rang\|nom\|mv-n`, `TW\|rang\|nom\|zonder-n`, `TW\|rang\|prenom\|stan`, `VG\|neven`, `VG\|onder`, `VNW\|aanw\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|aanw\|adv-pron\|stan\|red\|3\|getal`, `VNW\|aanw\|det\|dat\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|dat\|prenom\|met-e\|evmo`, `VNW\|aanw\|det\|gen\|prenom\|met-e\|rest3`, `VNW\|aanw\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|aanw\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|stan\|prenom\|met-e\|rest`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|agr`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|evon`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|rest`, `VNW\|aanw\|det\|stan\|vrij\|zonder`, `VNW\|aanw\|pron\|gen\|vol\|3m\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3o\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3\|getal`, `VNW\|betr\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|betr\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|betr\|pron\|stan\|vol\|3\|ev`, `VNW\|betr\|pron\|stan\|vol\|persoon\|getal`, `VNW\|bez\|det\|gen\|vol\|3\|ev\|prenom\|met-e\|rest3`, `VNW\|bez\|det\|stan\|nadr\|2v\|mv\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|zonder\|evon`, `VNW\|bez\|det\|stan\|vol\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|2\|getal\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3p\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3\|mv\|prenom\|zonder\|agr`, `VNW\|excl\|pron\|stan\|vol\|3\|getal`, `VNW\|onbep\|adv-pron\|gen\|red\|3\|getal`, `VNW\|onbep\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|onbep\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|onbep\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|onbep\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|agr`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|evz`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|mv`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|rest`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|agr`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|evon`, `VNW\|onbep\|det\|stan\|vrij\|zonder`, `VNW\|onbep\|grad\|gen\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|sup`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|comp`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|mv\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|basis`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|sup`, `VNW\|onbep\|pron\|gen\|vol\|3p\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3o\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3p\|ev`, `VNW\|pers\|pron\|gen\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|nomin\|nadr\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|red\|1\|mv`, `VNW\|pers\|pron\|nomin\|red\|2v\|ev`, `VNW\|pers\|pron\|nomin\|red\|2\|getal`, `VNW\|pers\|pron\|nomin\|red\|3p\|ev\|masc`, `VNW\|pers\|pron\|nomin\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|nomin\|vol\|1\|ev`, `VNW\|pers\|pron\|nomin\|vol\|1\|mv`, `VNW\|pers\|pron\|nomin\|vol\|2b\|getal`, `VNW\|pers\|pron\|nomin\|vol\|2v\|ev`, `VNW\|pers\|pron\|nomin\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|vol\|3p\|mv`, `VNW\|pers\|pron\|nomin\|vol\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|obl\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|2v\|ev`, `VNW\|pers\|pron\|obl\|vol\|3p\|mv`, `VNW\|pers\|pron\|obl\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|3\|getal\|fem`, `VNW\|pers\|pron\|stan\|nadr\|2v\|mv`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|fem`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|onz`, `VNW\|pers\|pron\|stan\|red\|3\|mv`, `VNW\|pr\|pron\|obl\|nadr\|1\|ev`, `VNW\|pr\|pron\|obl\|nadr\|2v\|getal`, `VNW\|pr\|pron\|obl\|nadr\|2\|getal`, `VNW\|pr\|pron\|obl\|red\|1\|ev`, `VNW\|pr\|pron\|obl\|red\|2v\|getal`, `VNW\|pr\|pron\|obl\|vol\|1\|ev`, `VNW\|pr\|pron\|obl\|vol\|1\|mv`, `VNW\|pr\|pron\|obl\|vol\|2\|getal`, `VNW\|recip\|pron\|gen\|vol\|persoon\|mv`, `VNW\|recip\|pron\|obl\|vol\|persoon\|mv`, `VNW\|refl\|pron\|obl\|nadr\|3\|getal`, `VNW\|refl\|pron\|obl\|red\|3\|getal`, `VNW\|vb\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|vb\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|vb\|det\|stan\|prenom\|met-e\|rest`, `VNW\|vb\|det\|stan\|prenom\|zonder\|evon`, `VNW\|vb\|pron\|gen\|vol\|3m\|ev`, `VNW\|vb\|pron\|gen\|vol\|3p\|mv`, `VNW\|vb\|pron\|gen\|vol\|3v\|ev`, `VNW\|vb\|pron\|stan\|vol\|3o\|ev`, `VNW\|vb\|pron\|stan\|vol\|3p\|getal`, `VZ\|fin`, `VZ\|init`, `VZ\|versm`, `WW\|inf\|nom\|zonder\|zonder-n`, `WW\|inf\|prenom\|met-e`, `WW\|inf\|vrij\|zonder`, `WW\|od\|nom\|met-e\|mv-n`, `WW\|od\|nom\|met-e\|zonder-n`, `WW\|od\|prenom\|met-e`, `WW\|od\|prenom\|zonder`, `WW\|od\|vrij\|zonder`, `WW\|pv\|conj\|ev`, `WW\|pv\|tgw\|ev`, `WW\|pv\|tgw\|met-t`, `WW\|pv\|tgw\|mv`, `WW\|pv\|verl\|ev`, `WW\|pv\|verl\|mv`, `WW\|vd\|nom\|met-e\|mv-n`, `WW\|vd\|nom\|met-e\|zonder-n`, `WW\|vd\|prenom\|met-e`, `WW\|vd\|prenom\|zonder`, `WW\|vd\|vrij\|zonder` |
 | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl`, `expl:pv`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `orphan`, `parataxis`, `punct`, `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>
@@ -92,22 +106,22 @@ Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, pa
 | Type | Score |
 | --- | --- |
 | `TOKEN_ACC` | 99.97 |
 | `TOKEN_P` | 99.74 |
 | `TOKEN_R` | 99.76 |
 | `TOKEN_F` | 99.75 |
-| `POS_ACC` | 96.67 |
-| `MORPH_ACC` | 96.49 |
-| `MORPH_MICRO_P` | 97.44 |
-| `MORPH_MICRO_R` | 95.59 |
-| `MORPH_MICRO_F` | 96.50 |
-| `TAG_ACC` | 95.43 |
-| `SENTS_P` | 86.63 |
-| `SENTS_R` | 88.81 |
-| `SENTS_F` | 87.71 |
-| `DEP_UAS` | 87.02 |
-| `DEP_LAS` | 82.61 |
-| `LEMMA_ACC` | 81.59 |
-| `ENTS_P` | 77.72 |
-| `ENTS_R` | 75.52 |
-| `ENTS_F` | 76.60 |

     metrics:
     - name: NER Precision
       type: precision
+      value: 0.7652916074
     - name: NER Recall
       type: recall
+      value: 0.7441217151
     - name: NER F Score
       type: f_score
+      value: 0.7545582048
+  - task:
+      name: TAG
+      type: token-classification
+    metrics:
+    - name: TAG (XPOS) Accuracy
+      type: accuracy
+      value: 0.9534133043
   - task:
       name: POS
       type: token-classification
     metrics:
+    - name: POS (UPOS) Accuracy
       type: accuracy
+      value: 0.9661941112
   - task:
+      name: MORPH
       type: token-classification
     metrics:
+    - name: Morph (UFeats) Accuracy
+      type: accuracy
+      value: 0.9635947213
   - task:
+      name: LEMMA
       type: token-classification
     metrics:
+    - name: Lemma Accuracy
       type: accuracy
+      value: 0.9417537126
+  - task:
+      name: UNLABELED_DEPENDENCIES
+      type: token-classification
+    metrics:
+    - name: Unlabeled Attachment Score (UAS)
+      type: f_score
+      value: 0.8698053923
   - task:
       name: LABELED_DEPENDENCIES
       type: token-classification
     metrics:
+    - name: Labeled Attachment Score (LAS)
+      type: f_score
+      value: 0.8235860531
+  - task:
+      name: SENTS
+      type: token-classification
+    metrics:
+    - name: Sentences F-Score
+      type: f_score
+      value: 0.8749559704
 ---
 ### Details: https://spacy.io/models/nl#nl_core_news_lg
+Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, parser, lemmatizer (trainable_lemmatizer), senter, ner.
 | Feature | Description |
 | --- | --- |
 | **Name** | `nl_core_news_lg` |
+| **Version** | `3.3.0` |
+| **spaCy** | `>=3.3.0.dev0,<3.4.0` |
+| **Default Pipeline** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `attribute_ruler`, `ner` |
+| **Components** | `tok2vec`, `morphologizer`, `tagger`, `parser`, `lemmatizer`, `senter`, `attribute_ruler`, `ner` |
 | **Vectors** | 500000 keys, 500000 unique vectors (300 dimensions) |
+| **Sources** | [UD Dutch LassySmall v2.8](https://github.com/UniversalDependencies/UD_Dutch-LassySmall) (Bouma, Gosse; van Noord, Gertjan)<br />[Dutch NER Annotations for UD LassySmall](https://nlp.town) (NLP Town)<br />[UD Dutch LassySmall v2.8](https://github.com/UniversalDependencies/UD_Dutch-LassySmall) (Bouma, Gosse; van Noord, Gertjan)<br />[UD Dutch Alpino v2.8](https://github.com/UniversalDependencies/UD_Dutch-Alpino) (Zeman, Daniel; Žabokrtský, Zdeněk; Bouma, Gosse; van Noord, Gertjan)<br />[Explosion fastText Vectors (cbow, OSCAR Common Crawl + Wikipedia)](https://spacy.io) (Explosion) |
 | **License** | `CC BY-SA 4.0` |
 | **Author** | [Explosion](https://explosion.ai) |
 <details>
+<summary>View label scheme (321 labels for 4 components)</summary>
 | Component | Labels |
 | --- | --- |
 | **`morphologizer`** | `POS=PRON\|Person=3\|PronType=Dem`, `Number=Sing\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=ADV`, `POS=VERB\|VerbForm=Part`, `POS=PUNCT`, `Number=Sing\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `POS=ADP`, `POS=NUM`, `Number=Plur\|POS=NOUN`, `POS=VERB\|VerbForm=Inf`, `POS=SCONJ`, `Definite=Def\|POS=DET`, `Gender=Com\|Number=Sing\|POS=NOUN`, `Number=Sing\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `Degree=Pos\|POS=ADJ`, `Gender=Neut\|Number=Sing\|POS=PROPN`, `Gender=Com\|Number=Sing\|POS=PROPN`, `POS=AUX\|VerbForm=Inf`, `Number=Sing\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `POS=DET`, `Gender=Neut\|Number=Sing\|POS=NOUN`, `POS=PRON\|Person=3\|PronType=Prs`, `POS=CCONJ`, `Number=Plur\|POS=VERB\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|Person=3\|PronType=Ind`, `Degree=Cmp\|POS=ADJ`, `Case=Nom\|POS=PRON\|Person=1\|PronType=Prs`, `Definite=Ind\|POS=DET`, `Case=Nom\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `Number=Plur\|POS=AUX\|Tense=Pres\|VerbForm=Fin`, `POS=PRON\|PronType=Rel`, `Case=Acc\|POS=PRON\|Person=1\|PronType=Prs`, `Number=Plur\|POS=VERB\|Tense=Past\|VerbForm=Fin`, `Gender=Com,Neut\|Number=Sing\|POS=NOUN`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs\|Reflex=Yes`, `Case=Acc\|POS=PRON\|Person=3\|PronType=Prs`, `POS=PROPN`, `POS=PRON\|PronType=Ind`, `POS=PRON\|Person=3\|PronType=Int`, `Case=Acc\|POS=PRON\|PronType=Rcp`, `Number=Plur\|POS=AUX\|Tense=Past\|VerbForm=Fin`, `Number=Sing\|POS=NOUN`, `POS=PRON\|Person=1\|Poss=Yes\|PronType=Prs`, `POS=SYM`, `Abbr=Yes\|POS=X`, `Gender=Com,Neut\|Number=Sing\|POS=PROPN`, `Degree=Sup\|POS=ADJ`, `POS=ADJ`, `Number=Sing\|POS=PROPN`, `POS=PRON\|PronType=Dem`, `POS=AUX\|VerbForm=Part`, `POS=PRON\|Person=3\|PronType=Rel`, `Number=Plur\|POS=PROPN`, `POS=PRON\|Person=2\|Poss=Yes\|PronType=Prs`, `Case=Dat\|POS=PRON\|PronType=Dem`, `Case=Nom\|POS=PRON\|Person=2\|PronType=Prs`, `POS=INTJ`, `Case=Acc\|POS=PRON\|Person=2\|PronType=Prs`, `Case=Gen\|POS=PRON\|Person=3\|Poss=Yes\|PronType=Prs`, `POS=PRON\|PronType=Int`, `POS=PRON\|Person=2\|PronType=Prs`, `POS=PRON\|Person=3`, `Case=Gen\|POS=PRON\|Person=2\|PronType=Prs`, `POS=X` |
 | **`tagger`** | `ADJ\|nom\|basis\|met-e\|mv-n`, `ADJ\|nom\|basis\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|basis\|met-e\|zonder-n\|stan`, `ADJ\|nom\|basis\|zonder\|mv-n`, `ADJ\|nom\|basis\|zonder\|zonder-n`, `ADJ\|nom\|comp\|met-e\|mv-n`, `ADJ\|nom\|comp\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|met-e\|mv-n`, `ADJ\|nom\|sup\|met-e\|zonder-n\|bijz`, `ADJ\|nom\|sup\|met-e\|zonder-n\|stan`, `ADJ\|nom\|sup\|zonder\|zonder-n`, `ADJ\|postnom\|basis\|met-s`, `ADJ\|postnom\|basis\|zonder`, `ADJ\|postnom\|comp\|met-s`, `ADJ\|prenom\|basis\|met-e\|bijz`, `ADJ\|prenom\|basis\|met-e\|stan`, `ADJ\|prenom\|basis\|zonder`, `ADJ\|prenom\|comp\|met-e\|stan`, `ADJ\|prenom\|comp\|zonder`, `ADJ\|prenom\|sup\|met-e\|stan`, `ADJ\|prenom\|sup\|zonder`, `ADJ\|vrij\|basis\|zonder`, `ADJ\|vrij\|comp\|zonder`, `ADJ\|vrij\|dim\|zonder`, `ADJ\|vrij\|sup\|zonder`, `BW`, `LET`, `LID\|bep\|dat\|evmo`, `LID\|bep\|gen\|evmo`, `LID\|bep\|gen\|rest3`, `LID\|bep\|stan\|evon`, `LID\|bep\|stan\|rest`, `LID\|onbep\|stan\|agr`, `N\|eigen\|ev\|basis\|gen`, `N\|eigen\|ev\|basis\|genus\|stan`, `N\|eigen\|ev\|basis\|onz\|stan`, `N\|eigen\|ev\|basis\|zijd\|stan`, `N\|eigen\|ev\|dim\|onz\|stan`, `N\|eigen\|mv\|basis`, `N\|soort\|ev\|basis\|dat`, `N\|soort\|ev\|basis\|gen`, `N\|soort\|ev\|basis\|genus\|stan`, `N\|soort\|ev\|basis\|onz\|stan`, `N\|soort\|ev\|basis\|zijd\|stan`, `N\|soort\|ev\|dim\|onz\|stan`, `N\|soort\|mv\|basis`, `N\|soort\|mv\|dim`, `SPEC\|afgebr`, `SPEC\|afk`, `SPEC\|deeleigen`, `SPEC\|enof`, `SPEC\|meta`, `SPEC\|symb`, `SPEC\|vreemd`, `TSW`, `TW\|hoofd\|nom\|mv-n\|basis`, `TW\|hoofd\|nom\|mv-n\|dim`, `TW\|hoofd\|nom\|zonder-n\|basis`, `TW\|hoofd\|nom\|zonder-n\|dim`, `TW\|hoofd\|prenom\|stan`, `TW\|hoofd\|vrij`, `TW\|rang\|nom\|mv-n`, `TW\|rang\|nom\|zonder-n`, `TW\|rang\|prenom\|stan`, `VG\|neven`, `VG\|onder`, `VNW\|aanw\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|aanw\|adv-pron\|stan\|red\|3\|getal`, `VNW\|aanw\|det\|dat\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|dat\|prenom\|met-e\|evmo`, `VNW\|aanw\|det\|gen\|prenom\|met-e\|rest3`, `VNW\|aanw\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|aanw\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|aanw\|det\|stan\|prenom\|met-e\|rest`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|agr`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|evon`, `VNW\|aanw\|det\|stan\|prenom\|zonder\|rest`, `VNW\|aanw\|det\|stan\|vrij\|zonder`, `VNW\|aanw\|pron\|gen\|vol\|3m\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3o\|ev`, `VNW\|aanw\|pron\|stan\|vol\|3\|getal`, `VNW\|betr\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|betr\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|betr\|pron\|stan\|vol\|3\|ev`, `VNW\|betr\|pron\|stan\|vol\|persoon\|getal`, `VNW\|bez\|det\|gen\|vol\|3\|ev\|prenom\|met-e\|rest3`, `VNW\|bez\|det\|stan\|nadr\|2v\|mv\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|red\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|1\|mv\|prenom\|zonder\|evon`, `VNW\|bez\|det\|stan\|vol\|2v\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|2\|getal\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3m\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3p\|mv\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|nom\|met-e\|zonder-n`, `VNW\|bez\|det\|stan\|vol\|3v\|ev\|prenom\|met-e\|rest`, `VNW\|bez\|det\|stan\|vol\|3\|ev\|prenom\|zonder\|agr`, `VNW\|bez\|det\|stan\|vol\|3\|mv\|prenom\|zonder\|agr`, `VNW\|excl\|pron\|stan\|vol\|3\|getal`, `VNW\|onbep\|adv-pron\|gen\|red\|3\|getal`, `VNW\|onbep\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|onbep\|det\|stan\|nom\|met-e\|mv-n`, `VNW\|onbep\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|onbep\|det\|stan\|nom\|zonder\|zonder-n`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|agr`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|evz`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|mv`, `VNW\|onbep\|det\|stan\|prenom\|met-e\|rest`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|agr`, `VNW\|onbep\|det\|stan\|prenom\|zonder\|evon`, `VNW\|onbep\|det\|stan\|vrij\|zonder`, `VNW\|onbep\|grad\|gen\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|mv-n\|sup`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|basis`, `VNW\|onbep\|grad\|stan\|nom\|met-e\|zonder-n\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|comp`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|agr\|sup`, `VNW\|onbep\|grad\|stan\|prenom\|met-e\|mv\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|basis`, `VNW\|onbep\|grad\|stan\|prenom\|zonder\|agr\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|basis`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|comp`, `VNW\|onbep\|grad\|stan\|vrij\|zonder\|sup`, `VNW\|onbep\|pron\|gen\|vol\|3p\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3o\|ev`, `VNW\|onbep\|pron\|stan\|vol\|3p\|ev`, `VNW\|pers\|pron\|gen\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|nomin\|nadr\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|red\|1\|mv`, `VNW\|pers\|pron\|nomin\|red\|2v\|ev`, `VNW\|pers\|pron\|nomin\|red\|2\|getal`, `VNW\|pers\|pron\|nomin\|red\|3p\|ev\|masc`, `VNW\|pers\|pron\|nomin\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|nomin\|vol\|1\|ev`, `VNW\|pers\|pron\|nomin\|vol\|1\|mv`, `VNW\|pers\|pron\|nomin\|vol\|2b\|getal`, `VNW\|pers\|pron\|nomin\|vol\|2v\|ev`, `VNW\|pers\|pron\|nomin\|vol\|2\|getal`, `VNW\|pers\|pron\|nomin\|vol\|3p\|mv`, `VNW\|pers\|pron\|nomin\|vol\|3v\|ev\|fem`, `VNW\|pers\|pron\|nomin\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|nadr\|3m\|ev\|masc`, `VNW\|pers\|pron\|obl\|red\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|2v\|ev`, `VNW\|pers\|pron\|obl\|vol\|3p\|mv`, `VNW\|pers\|pron\|obl\|vol\|3\|ev\|masc`, `VNW\|pers\|pron\|obl\|vol\|3\|getal\|fem`, `VNW\|pers\|pron\|stan\|nadr\|2v\|mv`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|fem`, `VNW\|pers\|pron\|stan\|red\|3\|ev\|onz`, `VNW\|pers\|pron\|stan\|red\|3\|mv`, `VNW\|pr\|pron\|obl\|nadr\|1\|ev`, `VNW\|pr\|pron\|obl\|nadr\|2v\|getal`, `VNW\|pr\|pron\|obl\|nadr\|2\|getal`, `VNW\|pr\|pron\|obl\|red\|1\|ev`, `VNW\|pr\|pron\|obl\|red\|2v\|getal`, `VNW\|pr\|pron\|obl\|vol\|1\|ev`, `VNW\|pr\|pron\|obl\|vol\|1\|mv`, `VNW\|pr\|pron\|obl\|vol\|2\|getal`, `VNW\|recip\|pron\|gen\|vol\|persoon\|mv`, `VNW\|recip\|pron\|obl\|vol\|persoon\|mv`, `VNW\|refl\|pron\|obl\|nadr\|3\|getal`, `VNW\|refl\|pron\|obl\|red\|3\|getal`, `VNW\|vb\|adv-pron\|obl\|vol\|3o\|getal`, `VNW\|vb\|det\|stan\|nom\|met-e\|zonder-n`, `VNW\|vb\|det\|stan\|prenom\|met-e\|rest`, `VNW\|vb\|det\|stan\|prenom\|zonder\|evon`, `VNW\|vb\|pron\|gen\|vol\|3m\|ev`, `VNW\|vb\|pron\|gen\|vol\|3p\|mv`, `VNW\|vb\|pron\|gen\|vol\|3v\|ev`, `VNW\|vb\|pron\|stan\|vol\|3o\|ev`, `VNW\|vb\|pron\|stan\|vol\|3p\|getal`, `VZ\|fin`, `VZ\|init`, `VZ\|versm`, `WW\|inf\|nom\|zonder\|zonder-n`, `WW\|inf\|prenom\|met-e`, `WW\|inf\|vrij\|zonder`, `WW\|od\|nom\|met-e\|mv-n`, `WW\|od\|nom\|met-e\|zonder-n`, `WW\|od\|prenom\|met-e`, `WW\|od\|prenom\|zonder`, `WW\|od\|vrij\|zonder`, `WW\|pv\|conj\|ev`, `WW\|pv\|tgw\|ev`, `WW\|pv\|tgw\|met-t`, `WW\|pv\|tgw\|mv`, `WW\|pv\|verl\|ev`, `WW\|pv\|verl\|mv`, `WW\|vd\|nom\|met-e\|mv-n`, `WW\|vd\|nom\|met-e\|zonder-n`, `WW\|vd\|prenom\|met-e`, `WW\|vd\|prenom\|zonder`, `WW\|vd\|vrij\|zonder` |
 | **`parser`** | `ROOT`, `acl`, `acl:relcl`, `advcl`, `advmod`, `amod`, `appos`, `aux`, `aux:pass`, `case`, `cc`, `ccomp`, `compound:prt`, `conj`, `cop`, `csubj`, `dep`, `det`, `expl`, `expl:pv`, `fixed`, `flat`, `iobj`, `mark`, `nmod`, `nmod:poss`, `nsubj`, `nsubj:pass`, `nummod`, `obj`, `obl`, `obl:agent`, `orphan`, `parataxis`, `punct`, `xcomp` |
 | **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PRODUCT`, `QUANTITY`, `TIME`, `WORK_OF_ART` |
 </details>
 | Type | Score |
 | --- | --- |
+| `TAG_ACC` | 95.34 |
+| `SENTS_P` | 85.95 |
+| `SENTS_R` | 89.10 |
+| `SENTS_F` | 87.50 |
+| `DEP_UAS` | 86.98 |
+| `DEP_LAS` | 82.36 |
+| `ENTS_P` | 76.53 |
+| `ENTS_R` | 74.41 |
+| `ENTS_F` | 75.46 |
 | `TOKEN_ACC` | 99.97 |
 | `TOKEN_P` | 99.74 |
 | `TOKEN_R` | 99.76 |
 | `TOKEN_F` | 99.75 |
+| `POS_ACC` | 96.62 |
+| `MORPH_ACC` | 96.36 |
+| `MORPH_MICRO_P` | 97.22 |
+| `MORPH_MICRO_R` | 95.52 |
+| `MORPH_MICRO_F` | 96.36 |
+| `LEMMA_ACC` | 94.18 |

accuracy.json CHANGED Viewed

@@ -1,339 +1,262 @@
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-  "morph_micro_r": 0.9558803442,
-  "morph_micro_f": 0.9650417155,
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     "orphan": {
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   "ents_per_type": {
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     },
-    "GPE": {
-      "p": 0.785046729,
-      "r": 0.9230769231,
-      "f": 0.8484848485
     },
     "QUANTITY": {
-      "p": 0.8571428571,
-      "r": 1.0,
-      "f": 0.9230769231
     },
-    "PERCENT": {
-      "p": 1.0,
-      "r": 0.8333333333,
-      "f": 0.9090909091
     },
-    "PERSON": {
-      "p": 0.7788778878,
-      "r": 0.7637540453,
-      "f": 0.7712418301
     },
-    "LAW": {
-      "p": 1.0,
-      "r": 0.3333333333,
-      "f": 0.5
     },
     "EVENT": {
-      "p": 0.4761904762,
-      "r": 0.4347826087,
-      "f": 0.4545454545
     },
-    "WORK_OF_ART": {
-      "p": 0.5882352941,
-      "r": 0.4444444444,
-      "f": 0.5063291139
     },
     "ORDINAL": {
-      "p": 0.96875,
-      "r": 0.9393939394,
-      "f": 0.9538461538
     },
     "LANGUAGE": {
-      "p": 0.75,
-      "r": 0.8181818182,
-      "f": 0.7826086957
     },
     "LOC": {
-      "p": 0.5333333333,
-      "r": 0.2352941176,
-      "f": 0.3265306122
     },
-    "FAC": {
-      "p": 0.1,
-      "r": 0.2142857143,
-      "f": 0.1363636364
     },
-    "PRODUCT": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
@@ -343,11 +266,88 @@
       "r": 0.0,
       "f": 0.0
     },
-    "TIME": {
       "p": 1.0,
       "r": 1.0,
       "f": 1.0
     }
   },
-  "speed": 3053.5292904657
 }

 {
+  "tag_acc": 0.9534133043,
+  "sents_p": 0.8595155709,
+  "sents_r": 0.8909612626,
+  "sents_f": 0.8749559704,
+  "dep_uas": 0.8698053923,
+  "dep_las": 0.8235860531,
   "dep_las_per_type": {
+    "nmod:poss": {
+      "p": 0.9456521739,
+      "r": 0.9525547445,
+      "f": 0.9490909091
     },
     "nsubj": {
+      "p": 0.8466494845,
+      "r": 0.8639053254,
+      "f": 0.8551903677
     },
+    "aux": {
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+      "r": 0.9013157895,
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+    "advmod": {
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+      "r": 0.8952654232,
+      "f": 0.8791828108
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+    "det": {
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     },
     "mark": {
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+      "f": 0.8913043478
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+    "ccomp": {
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+      "f": 0.6820276498
     },
+    "case": {
+      "p": 0.9379652605,
+      "r": 0.9606099111,
+      "f": 0.9491525424
     },
+    "appos": {
+      "p": 0.7060702875,
+      "r": 0.6696969697,
+      "f": 0.6874027994
     },
+    "obj": {
+      "p": 0.7875968992,
+      "r": 0.7755725191,
+      "f": 0.7815384615
     },
+    "compound:prt": {
+      "p": 0.7755102041,
+      "r": 0.7136150235,
+      "f": 0.7432762836
     },
+    "xcomp": {
+      "p": 0.6765799257,
+      "r": 0.6618181818,
+      "f": 0.6691176471
     },
     "flat": {
+      "p": 0.8115124153,
+      "r": 0.7624602333,
+      "f": 0.7862219792
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+    "expl:pv": {
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+      "r": 0.3673469388,
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+    "advcl": {
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+      "r": 0.454954955,
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     "nsubj:pass": {
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     "aux:pass": {
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+      "f": 0.9226666667
     },
+    "iobj": {
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+    "cop": {
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     "parataxis": {
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+      "r": 0.268115942,
+      "f": 0.309623431
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+    "acl:relcl": {
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+      "r": 0.7044025157,
+      "f": 0.7
     },
+    "fixed": {
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+      "f": 0.5679824561
     },
+    "obl:agent": {
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+      "f": 0.9090909091
+    },
+    "expl": {
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+      "f": 0.4347826087
+    },
+    "csubj": {
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     },
     "dep": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     },
     "orphan": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
     }
   },
+  "ents_p": 0.7652916074,
+  "ents_r": 0.7441217151,
+  "ents_f": 0.7545582048,
   "ents_per_type": {
     "ORG": {
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     },
+    "PERSON": {
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     },
     "QUANTITY": {
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     },
+    "CARDINAL": {
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     },
+    "NORP": {
+      "p": 0.0,
+      "r": 0.0,
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+    "DATE": {
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     },
     "EVENT": {
+      "p": 0.0,
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+      "f": 0.0
     },
+    "PRODUCT": {
+      "p": 0.0,
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+    },
+    "GPE": {
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+      "r": 0.0,
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     },
     "ORDINAL": {
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+      "f": 0.0
     },
     "LANGUAGE": {
+      "p": 0.0,
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+      "f": 0.0
+    },
+    "TIME": {
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     },
     "LOC": {
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+      "f": 0.0
     },
+    "WORK_OF_ART": {
+      "p": 0.0,
+      "r": 0.0,
+      "f": 0.0
     },
+    "FAC": {
       "p": 0.0,
       "r": 0.0,
       "f": 0.0
       "r": 0.0,
       "f": 0.0
     },
+    "PERCENT": {
+      "p": 0.0,
+      "r": 0.0,
+      "f": 0.0
+    },
+    "LAW": {
+      "p": 0.0,
+      "r": 0.0,
+      "f": 0.0
+    }
+  },
+  "speed": 10256.4374458498,
+  "token_acc": 0.9997165842,
+  "token_p": 0.9974281853,
+  "token_r": 0.9975586363,
+  "token_f": 0.9974934066,
+  "pos_acc": 0.9661941112,
+  "morph_acc": 0.9635947213,
+  "morph_micro_p": 0.9722389581,
+  "morph_micro_r": 0.9551518463,
+  "morph_micro_f": 0.9636196601,
+  "morph_per_feat": {
+    "Person": {
+      "p": 0.9892891918,
+      "r": 0.9713193117,
+      "f": 0.9802219006
+    },
+    "Poss": {
+      "p": 0.9811320755,
+      "r": 0.9961685824,
+      "f": 0.9885931559
+    },
+    "PronType": {
+      "p": 0.9880647911,
+      "r": 0.9634247714,
+      "f": 0.9755892256
+    },
+    "Gender": {
+      "p": 0.9345253747,
+      "r": 0.90409565,
+      "f": 0.9190587018
+    },
+    "Number": {
+      "p": 0.9816793893,
+      "r": 0.9624307738,
+      "f": 0.9719597914
+    },
+    "Tense": {
+      "p": 0.9805339266,
+      "r": 0.9692138538,
+      "f": 0.9748410285
+    },
+    "VerbForm": {
+      "p": 0.9623188406,
+      "r": 0.9557394746,
+      "f": 0.9590178733
+    },
+    "Degree": {
+      "p": 0.9655677656,
+      "r": 0.9468390805,
+      "f": 0.9561117156
+    },
+    "Definite": {
+      "p": 0.9942680776,
+      "r": 0.9925176056,
+      "f": 0.9933920705
+    },
+    "Case": {
+      "p": 0.998,
+      "r": 0.9940239044,
+      "f": 0.996007984
+    },
+    "Reflex": {
       "p": 1.0,
       "r": 1.0,
       "f": 1.0
+    },
+    "Abbr": {
+      "p": 1.0,
+      "r": 0.5,
+      "f": 0.6666666667
     }
   },
+  "lemma_acc": 0.9417537126
 }

attribute_ruler/patterns CHANGED Viewed

Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ

config.cfg CHANGED Viewed

@@ -10,7 +10,7 @@ seed = 0
 [nlp]
 lang = "nl"
-pipeline = ["tok2vec","morphologizer","tagger","parser","senter","attribute_ruler","lemmatizer","ner"]
 disabled = ["senter"]
 before_creation = null
 after_creation = null
@@ -26,11 +26,22 @@ scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
 validate = false
 [components.lemmatizer]
-factory = "lemmatizer"
-mode = "rule"
-model = null
 overwrite = false
 scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
 [components.morphologizer]
 factory = "morphologizer"
@@ -39,8 +50,9 @@ overwrite = true
 scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
 [components.morphologizer.model]
-@architectures = "spacy.Tagger.v1"
 nO = null
 [components.morphologizer.model.tok2vec]
 @architectures = "spacy.Tok2VecListener.v1"
@@ -70,7 +82,7 @@ nO = null
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,2500,2500,2500,100]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
@@ -108,8 +120,9 @@ overwrite = false
 scorer = {"@scorers":"spacy.senter_scorer.v1"}
 [components.senter.model]
-@architectures = "spacy.Tagger.v1"
 nO = null
 [components.senter.model.tok2vec]
 @architectures = "spacy.Tok2Vec.v2"
@@ -130,12 +143,14 @@ maxout_pieces = 2
 [components.tagger]
 factory = "tagger"
 overwrite = false
 scorer = {"@scorers":"spacy.tagger_scorer.v1"}
 [components.tagger.model]
-@architectures = "spacy.Tagger.v1"
 nO = null
 [components.tagger.model.tok2vec]
 @architectures = "spacy.Tok2VecListener.v1"
@@ -152,7 +167,7 @@ factory = "tok2vec"
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode:width}
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
-rows = [5000,2500,2500,2500,100]
 include_static_vectors = true
 [components.tok2vec.model.encode]
@@ -189,7 +204,7 @@ dropout = 0.1
 accumulate_gradient = 1
 patience = 5000
 max_epochs = 0
-max_steps = 0
 eval_frequency = 1000
 frozen_components = []
 before_to_disk = null
@@ -224,18 +239,18 @@ eps = 0.00000001
 learn_rate = 0.001
 [training.score_weights]
-pos_acc = 0.06
-morph_acc = 0.05
 morph_per_feat = null
-tag_acc = 0.06
 dep_uas = 0.0
-dep_las = 0.16
 dep_las_per_type = null
 sents_p = null
 sents_r = null
-sents_f = 0.02
-lemma_acc = 0.5
-ents_f = 0.16
 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null
@@ -252,6 +267,13 @@ after_init = null
 [initialize.components]
 [initialize.components.morphologizer]
 [initialize.components.morphologizer.labels]

 [nlp]
 lang = "nl"
+pipeline = ["tok2vec","morphologizer","tagger","parser","lemmatizer","senter","attribute_ruler","ner"]
 disabled = ["senter"]
 before_creation = null
 after_creation = null
 validate = false
 [components.lemmatizer]
+factory = "trainable_lemmatizer"
+backoff = "orth"
+min_tree_freq = 3
 overwrite = false
 scorer = {"@scorers":"spacy.lemmatizer_scorer.v1"}
+top_k = 1
+[components.lemmatizer.model]
+@architectures = "spacy.Tagger.v2"
+nO = null
+normalize = false
+[components.lemmatizer.model.tok2vec]
+@architectures = "spacy.Tok2VecListener.v1"
+width = ${components.tok2vec.model.encode:width}
+upstream = "tok2vec"
 [components.morphologizer]
 factory = "morphologizer"
 scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
 [components.morphologizer.model]
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 [components.morphologizer.model.tok2vec]
 @architectures = "spacy.Tok2VecListener.v1"
 @architectures = "spacy.MultiHashEmbed.v2"
 width = 96
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
+rows = [5000,1000,2500,2500,50]
 include_static_vectors = true
 [components.ner.model.tok2vec.encode]
 scorer = {"@scorers":"spacy.senter_scorer.v1"}
 [components.senter.model]
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 [components.senter.model.tok2vec]
 @architectures = "spacy.Tok2Vec.v2"
 [components.tagger]
 factory = "tagger"
+neg_prefix = "!"
 overwrite = false
 scorer = {"@scorers":"spacy.tagger_scorer.v1"}
 [components.tagger.model]
+@architectures = "spacy.Tagger.v2"
 nO = null
+normalize = false
 [components.tagger.model.tok2vec]
 @architectures = "spacy.Tok2VecListener.v1"
 @architectures = "spacy.MultiHashEmbed.v2"
 width = ${components.tok2vec.model.encode:width}
 attrs = ["NORM","PREFIX","SUFFIX","SHAPE","SPACY"]
+rows = [5000,1000,2500,2500,50]
 include_static_vectors = true
 [components.tok2vec.model.encode]
 accumulate_gradient = 1
 patience = 5000
 max_epochs = 0
+max_steps = 100000
 eval_frequency = 1000
 frozen_components = []
 before_to_disk = null
 learn_rate = 0.001
 [training.score_weights]
+pos_acc = 0.1
+morph_acc = 0.09
 morph_per_feat = null
+tag_acc = 0.1
 dep_uas = 0.0
+dep_las = 0.29
 dep_las_per_type = null
 sents_p = null
 sents_r = null
+sents_f = 0.04
+lemma_acc = 0.1
+ents_f = 0.29
 ents_p = 0.0
 ents_r = 0.0
 ents_per_type = null
 [initialize.components]
+[initialize.components.lemmatizer]
+[initialize.components.lemmatizer.labels]
+@readers = "spacy.read_labels.v1"
+path = "corpus/labels/trainable_lemmatizer.json"
+require = false
 [initialize.components.morphologizer]
 [initialize.components.morphologizer.labels]

lemmatizer/cfg ADDED Viewed

	@@ -0,0 +1,1198 @@

+{
+  "labels":[
+    1,
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+}

lemmatizer/{lookups/lookups.bin → model} RENAMED Viewed

@@ -1,3 +1,3 @@
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lemmatizer/trees ADDED Viewed

Binary file (288 kB). View file

meta.json CHANGED Viewed

@@ -1,14 +1,14 @@
 {
   "lang":"nl",
   "name":"core_news_lg",
-  "version":"3.2.0",
-  "description":"Dutch pipeline optimized for CPU. Components: tok2vec, morphologizer, tagger, parser, senter, ner, attribute_ruler, lemmatizer.",
   "author":"Explosion",
   "email":"contact@explosion.ai",
   "url":"https://explosion.ai",
   "license":"CC BY-SA 4.0",
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