osanseviero
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Commit
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Parent(s):
7ed6818
Update spaCy pipeline
Browse files- LICENSES_SOURCES +2 -2
- README.md +36 -28
- accuracy.json +155 -138
- attribute_ruler/patterns +0 -0
- config.cfg +47 -18
- ja_core_news_md-any-py3-none-any.whl +2 -2
- meta.json +184 -144
- morphologizer/cfg +46 -0
- morphologizer/model +3 -0
- ner/model +0 -0
- ner/moves +1 -1
- parser/model +0 -0
- parser/moves +1 -1
- senter/cfg +1 -1
- senter/model +0 -0
- tok2vec/model +0 -0
- vocab/strings.json +2 -2
- vocab/vectors.cfg +3 -0
LICENSES_SOURCES
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# UD Japanese GSD v2.
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* Author: Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel
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* URL: https://github.com/UniversalDependencies/UD_Japanese-GSD
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# UD Japanese GSD v2.
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* Author: Megagon Labs Tokyo
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* URL: https://github.com/megagonlabs/UD_Japanese-GSD
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# UD Japanese GSD v2.8
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* Author: Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel
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* URL: https://github.com/UniversalDependencies/UD_Japanese-GSD
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# UD Japanese GSD v2.8 NER
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* Author: Megagon Labs Tokyo
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* URL: https://github.com/megagonlabs/UD_Japanese-GSD
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README.md
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- token-classification
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language:
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- ja
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license:
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model-index:
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- name: ja_core_news_md
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results:
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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 Accuracy
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type: accuracy
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value: 0.
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- task:
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name: SENTER
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type: token-classification
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metrics:
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- name: SENTER Precision
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type: precision
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value: 0.
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- name: SENTER Recall
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type: recall
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value: 0.
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- name: SENTER 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: UNLABELED_DEPENDENCIES
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type: token-classification
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metrics:
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- name: Unlabeled Dependencies Accuracy
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type: accuracy
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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 Dependencies Accuracy
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type: accuracy
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value: 0.
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---
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### Details: https://spacy.io/models/ja#ja_core_news_md
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Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.
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| Feature | Description |
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| --- | --- |
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| **Name** | `ja_core_news_md` |
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| **Version** | `3.
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| **spaCy** | `>=3.
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| **Default Pipeline** | `tok2vec`, `parser`, `attribute_ruler`, `ner` |
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| **Components** | `tok2vec`, `parser`, `senter`, `attribute_ruler`, `ner` |
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| **Vectors** | 480443 keys, 20000 unique vectors (300 dimensions) |
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| **Sources** | [UD Japanese GSD v2.
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| **License** | `CC BY-SA 4.0` |
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| **Author** | [Explosion](https://explosion.ai) |
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<details>
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<summary>View label scheme (
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| Component | Labels |
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| --- | --- |
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| **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `aux`, `case`, `cc`, `ccomp`, `compound`, `cop`, `csubj`, `dep`, `det`, `dislocated`, `fixed`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `punct` |
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| **`senter`** | `I`, `S` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `MOVEMENT`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PET_NAME`, `PHONE`, `PRODUCT`, `QUANTITY`, `TIME`, `TITLE_AFFIX`, `WORK_OF_ART` |
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| Type | Score |
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| --- | --- |
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| `TOKEN_ACC` | 99.69 |
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| `
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| `
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| `
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| `
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| `SENTS_P` |
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| `SENTS_R` | 99.
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| `SENTS_F` |
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- token-classification
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language:
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- ja
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license: cc-by-sa-4.0
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model-index:
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- name: ja_core_news_md
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results:
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metrics:
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- name: NER Precision
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type: precision
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value: 0.737704918
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- name: NER Recall
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type: recall
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value: 0.679245283
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- name: NER F Score
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type: f_score
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value: 0.7072691552
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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 Accuracy
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type: accuracy
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value: 0.9715755942
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- task:
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name: SENTER
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type: token-classification
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metrics:
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- name: SENTER Precision
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type: precision
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value: 0.9862475442
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- name: SENTER Recall
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type: recall
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+
value: 0.9901380671
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- name: SENTER F Score
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type: f_score
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value: 0.9881889764
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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 Dependencies Accuracy
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type: accuracy
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value: 0.9224188392
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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 Dependencies Accuracy
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type: accuracy
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value: 0.9224188392
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---
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### Details: https://spacy.io/models/ja#ja_core_news_md
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Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler.
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| Feature | Description |
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| --- | --- |
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| **Name** | `ja_core_news_md` |
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| **Version** | `3.2.0` |
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| **spaCy** | `>=3.2.0,<3.3.0` |
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| **Default Pipeline** | `tok2vec`, `morphologizer`, `parser`, `attribute_ruler`, `ner` |
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| **Components** | `tok2vec`, `morphologizer`, `parser`, `senter`, `attribute_ruler`, `ner` |
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| **Vectors** | 480443 keys, 20000 unique vectors (300 dimensions) |
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| **Sources** | [UD Japanese GSD v2.8](https://github.com/UniversalDependencies/UD_Japanese-GSD) (Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel)<br />[UD Japanese GSD v2.8 NER](https://github.com/megagonlabs/UD_Japanese-GSD) (Megagon Labs Tokyo)<br />[chiVe: Japanese Word Embedding with Sudachi & NWJC (chive-1.1-mc90-500k)](https://github.com/WorksApplications/chiVe) (Works Applications) |
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| **License** | `CC BY-SA 4.0` |
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| **Author** | [Explosion](https://explosion.ai) |
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<details>
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<summary>View label scheme (66 labels for 4 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`morphologizer`** | `POS=NOUN`, `POS=ADP`, `POS=VERB`, `POS=SCONJ`, `POS=AUX`, `POS=PUNCT`, `POS=PART`, `POS=DET`, `POS=NUM`, `POS=ADV`, `POS=PRON`, `POS=ADJ`, `POS=PROPN`, `POS=CCONJ`, `POS=SYM`, `POS=NOUN\|Polarity=Neg`, `POS=AUX\|Polarity=Neg`, `POS=INTJ`, `POS=SCONJ\|Polarity=Neg` |
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| **`parser`** | `ROOT`, `acl`, `advcl`, `advmod`, `amod`, `aux`, `case`, `cc`, `ccomp`, `compound`, `cop`, `csubj`, `dep`, `det`, `dislocated`, `fixed`, `mark`, `nmod`, `nsubj`, `nummod`, `obj`, `obl`, `punct` |
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| **`senter`** | `I`, `S` |
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| **`ner`** | `CARDINAL`, `DATE`, `EVENT`, `FAC`, `GPE`, `LANGUAGE`, `LAW`, `LOC`, `MONEY`, `MOVEMENT`, `NORP`, `ORDINAL`, `ORG`, `PERCENT`, `PERSON`, `PET_NAME`, `PHONE`, `PRODUCT`, `QUANTITY`, `TIME`, `TITLE_AFFIX`, `WORK_OF_ART` |
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| Type | Score |
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| --- | --- |
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| `TOKEN_ACC` | 99.69 |
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| `TOKEN_P` | 97.65 |
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| `TOKEN_R` | 97.90 |
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| `TOKEN_F` | 97.77 |
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| `POS_ACC` | 97.13 |
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| `MORPH_ACC` | 0.40 |
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| `MORPH_MICRO_P` | 34.01 |
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| `MORPH_MICRO_R` | 98.04 |
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| `MORPH_MICRO_F` | 50.51 |
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| `SENTS_P` | 98.62 |
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| `SENTS_R` | 99.01 |
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| `SENTS_F` | 98.82 |
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| `DEP_UAS` | 92.24 |
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| `DEP_LAS` | 90.75 |
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| `TAG_ACC` | 97.16 |
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| `LEMMA_ACC` | 96.59 |
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| `ENTS_P` | 73.77 |
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| `ENTS_R` | 67.92 |
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| `ENTS_F` | 70.73 |
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accuracy.json
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"sents_p": 0.994,
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"speed": 13117.9406369597,
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"morph_per_feat": {
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"Polarity": {
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"p": 0.0,
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"dep_las_per_type": {
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"cc": {
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"r": 0.8728522337,
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"ORG": {
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"TITLE_AFFIX": {
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"GPE": {
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"TIME": {
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"p": 0.6666666667,
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"QUANTITY": {
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"WORK_OF_ART": {
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-
"p": 0.
|
187 |
"r": 0.7058823529,
|
188 |
-
"f": 0.
|
189 |
},
|
190 |
"FAC": {
|
191 |
-
"p": 0.
|
192 |
-
"r": 0.
|
193 |
-
"f": 0.
|
194 |
-
},
|
195 |
-
"EVENT": {
|
196 |
-
"p": 0.8571428571,
|
197 |
-
"r": 0.4615384615,
|
198 |
-
"f": 0.6
|
199 |
},
|
200 |
"PERCENT": {
|
201 |
"p": 1.0,
|
202 |
"r": 0.2857142857,
|
203 |
"f": 0.4444444444
|
204 |
},
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
205 |
"LOC": {
|
206 |
-
"p": 0.
|
207 |
-
"r": 0.
|
208 |
-
"f": 0.
|
209 |
},
|
210 |
"MOVEMENT": {
|
211 |
"p": 0.0,
|
@@ -213,24 +234,20 @@
|
|
213 |
"f": 0.0
|
214 |
},
|
215 |
"LAW": {
|
216 |
-
"p":
|
217 |
-
"r": 0.
|
218 |
-
"f": 0.
|
219 |
},
|
220 |
"MONEY": {
|
221 |
-
"p":
|
222 |
"r": 1.0,
|
223 |
-
"f":
|
224 |
},
|
225 |
"LANGUAGE": {
|
226 |
-
"p":
|
227 |
"r": 1.0,
|
228 |
-
"f":
|
229 |
-
},
|
230 |
-
"CARDINAL": {
|
231 |
-
"p": 0.0,
|
232 |
-
"r": 0.0,
|
233 |
-
"f": 0.0
|
234 |
}
|
235 |
-
}
|
|
|
236 |
}
|
|
|
1 |
{
|
2 |
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3 |
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|
|
|
|
|
|
|
|
|
11 |
"morph_per_feat": {
|
12 |
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|
13 |
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|
14 |
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16 |
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20 |
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21 |
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|
23 |
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|
24 |
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|
25 |
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26 |
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27 |
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|
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|
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|
|
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|
|
|
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|
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|
39 |
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|
40 |
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|
41 |
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|
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|
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|
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108 |
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|
111 |
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|
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114 |
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115 |
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|
116 |
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117 |
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118 |
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|
121 |
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|
122 |
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|
123 |
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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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},
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129 |
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"det": {
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|
131 |
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|
132 |
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|
133 |
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|
134 |
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|
135 |
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|
136 |
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|
137 |
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"f": 0.72
|
138 |
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|
139 |
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|
140 |
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|
141 |
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|
142 |
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|
|
|
|
|
|
|
|
|
|
|
143 |
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|
144 |
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|
145 |
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|
146 |
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|
147 |
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|
148 |
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|
149 |
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|
150 |
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|
151 |
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152 |
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|
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|
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|
|
|
|
|
|
|
|
|
|
|
155 |
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|
156 |
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|
157 |
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|
158 |
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|
159 |
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|
160 |
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|
161 |
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|
162 |
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|
163 |
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|
164 |
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|
165 |
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},
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166 |
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167 |
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|
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|
169 |
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|
170 |
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|
171 |
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|
172 |
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|
173 |
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|
174 |
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|
175 |
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|
176 |
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|
177 |
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|
178 |
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|
179 |
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"f": 0.4931506849
|
180 |
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|
181 |
"TIME": {
|
182 |
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|
|
|
184 |
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|
185 |
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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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|
191 |
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|
192 |
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|
193 |
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|
194 |
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|
195 |
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|
196 |
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|
197 |
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|
198 |
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"r": 0.6818181818,
|
199 |
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"f": 0.6
|
200 |
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|
201 |
"WORK_OF_ART": {
|
202 |
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|
203 |
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|
204 |
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|
205 |
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|
206 |
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|
207 |
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|
208 |
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"r": 0.3513513514,
|
209 |
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"f": 0.4482758621
|
|
|
|
|
|
|
|
|
|
|
210 |
},
|
211 |
"PERCENT": {
|
212 |
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|
213 |
"r": 0.2857142857,
|
214 |
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|
215 |
},
|
216 |
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"CARDINAL": {
|
217 |
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"p": 0.0,
|
218 |
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"r": 0.0,
|
219 |
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"f": 0.0
|
220 |
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},
|
221 |
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"EVENT": {
|
222 |
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"p": 0.75,
|
223 |
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"r": 0.6923076923,
|
224 |
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"f": 0.72
|
225 |
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},
|
226 |
"LOC": {
|
227 |
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"p": 0.5333333333,
|
228 |
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"r": 0.8,
|
229 |
+
"f": 0.64
|
230 |
},
|
231 |
"MOVEMENT": {
|
232 |
"p": 0.0,
|
|
|
234 |
"f": 0.0
|
235 |
},
|
236 |
"LAW": {
|
237 |
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"p": 1.0,
|
238 |
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"r": 0.3333333333,
|
239 |
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"f": 0.5
|
240 |
},
|
241 |
"MONEY": {
|
242 |
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"p": 0.875,
|
243 |
"r": 1.0,
|
244 |
+
"f": 0.9333333333
|
245 |
},
|
246 |
"LANGUAGE": {
|
247 |
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"p": 0.8571428571,
|
248 |
"r": 1.0,
|
249 |
+
"f": 0.9230769231
|
|
|
|
|
|
|
|
|
|
|
250 |
}
|
251 |
+
},
|
252 |
+
"speed": 4621.4641630782
|
253 |
}
|
attribute_ruler/patterns
CHANGED
Binary files a/attribute_ruler/patterns and b/attribute_ruler/patterns differ
|
|
config.cfg
CHANGED
@@ -1,10 +1,8 @@
|
|
1 |
[paths]
|
2 |
-
train =
|
3 |
-
dev =
|
4 |
-
vectors =
|
5 |
-
raw = null
|
6 |
init_tok2vec = null
|
7 |
-
vocab_data = null
|
8 |
|
9 |
[system]
|
10 |
gpu_allocator = null
|
@@ -12,7 +10,7 @@ seed = 0
|
|
12 |
|
13 |
[nlp]
|
14 |
lang = "ja"
|
15 |
-
pipeline = ["tok2vec","parser","senter","attribute_ruler","ner"]
|
16 |
disabled = ["senter"]
|
17 |
before_creation = null
|
18 |
after_creation = null
|
@@ -27,12 +25,29 @@ split_mode = null
|
|
27 |
|
28 |
[components.attribute_ruler]
|
29 |
factory = "attribute_ruler"
|
|
|
30 |
validate = false
|
31 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
[components.ner]
|
33 |
factory = "ner"
|
34 |
incorrect_spans_key = null
|
35 |
moves = null
|
|
|
36 |
update_with_oracle_cut_size = 100
|
37 |
|
38 |
[components.ner.model]
|
@@ -66,6 +81,7 @@ factory = "parser"
|
|
66 |
learn_tokens = false
|
67 |
min_action_freq = 30
|
68 |
moves = null
|
|
|
69 |
update_with_oracle_cut_size = 100
|
70 |
|
71 |
[components.parser.model]
|
@@ -84,6 +100,8 @@ upstream = "tok2vec"
|
|
84 |
|
85 |
[components.senter]
|
86 |
factory = "senter"
|
|
|
|
|
87 |
|
88 |
[components.senter.model]
|
89 |
@architectures = "spacy.Tagger.v1"
|
@@ -130,17 +148,17 @@ maxout_pieces = 3
|
|
130 |
|
131 |
[corpora.dev]
|
132 |
@readers = "spacy.Corpus.v1"
|
133 |
-
|
134 |
-
max_length = 0
|
135 |
-
path = ${paths:dev}
|
136 |
gold_preproc = false
|
|
|
|
|
137 |
augmenter = null
|
138 |
|
139 |
[corpora.train]
|
140 |
@readers = "spacy.Corpus.v1"
|
141 |
-
path = ${paths
|
142 |
-
max_length = 5000
|
143 |
gold_preproc = false
|
|
|
144 |
limit = 0
|
145 |
augmenter = null
|
146 |
|
@@ -173,9 +191,8 @@ compound = 1.001
|
|
173 |
t = 0.0
|
174 |
|
175 |
[training.logger]
|
176 |
-
@loggers = "spacy.
|
177 |
-
|
178 |
-
remove_config_values = []
|
179 |
|
180 |
[training.optimizer]
|
181 |
@optimizers = "Adam.v1"
|
@@ -189,21 +206,26 @@ eps = 0.00000001
|
|
189 |
learn_rate = 0.001
|
190 |
|
191 |
[training.score_weights]
|
|
|
|
|
|
|
192 |
dep_uas = 0.0
|
193 |
-
dep_las = 0.
|
194 |
dep_las_per_type = null
|
195 |
sents_p = null
|
196 |
sents_r = null
|
197 |
-
sents_f = 0.
|
198 |
-
ents_f = 0.
|
199 |
ents_p = 0.0
|
200 |
ents_r = 0.0
|
201 |
ents_per_type = null
|
|
|
|
|
202 |
|
203 |
[pretraining]
|
204 |
|
205 |
[initialize]
|
206 |
-
vocab_data =
|
207 |
vectors = ${paths.vectors}
|
208 |
init_tok2vec = ${paths.init_tok2vec}
|
209 |
before_init = null
|
@@ -211,6 +233,13 @@ after_init = null
|
|
211 |
|
212 |
[initialize.components]
|
213 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
214 |
[initialize.components.ner]
|
215 |
|
216 |
[initialize.components.ner.labels]
|
|
|
1 |
[paths]
|
2 |
+
train = null
|
3 |
+
dev = null
|
4 |
+
vectors = null
|
|
|
5 |
init_tok2vec = null
|
|
|
6 |
|
7 |
[system]
|
8 |
gpu_allocator = null
|
|
|
10 |
|
11 |
[nlp]
|
12 |
lang = "ja"
|
13 |
+
pipeline = ["tok2vec","morphologizer","parser","senter","attribute_ruler","ner"]
|
14 |
disabled = ["senter"]
|
15 |
before_creation = null
|
16 |
after_creation = null
|
|
|
25 |
|
26 |
[components.attribute_ruler]
|
27 |
factory = "attribute_ruler"
|
28 |
+
scorer = {"@scorers":"spacy.attribute_ruler_scorer.v1"}
|
29 |
validate = false
|
30 |
|
31 |
+
[components.morphologizer]
|
32 |
+
factory = "morphologizer"
|
33 |
+
extend = true
|
34 |
+
overwrite = true
|
35 |
+
scorer = {"@scorers":"spacy.morphologizer_scorer.v1"}
|
36 |
+
|
37 |
+
[components.morphologizer.model]
|
38 |
+
@architectures = "spacy.Tagger.v1"
|
39 |
+
nO = null
|
40 |
+
|
41 |
+
[components.morphologizer.model.tok2vec]
|
42 |
+
@architectures = "spacy.Tok2VecListener.v1"
|
43 |
+
width = ${components.tok2vec.model.encode:width}
|
44 |
+
upstream = "tok2vec"
|
45 |
+
|
46 |
[components.ner]
|
47 |
factory = "ner"
|
48 |
incorrect_spans_key = null
|
49 |
moves = null
|
50 |
+
scorer = {"@scorers":"spacy.ner_scorer.v1"}
|
51 |
update_with_oracle_cut_size = 100
|
52 |
|
53 |
[components.ner.model]
|
|
|
81 |
learn_tokens = false
|
82 |
min_action_freq = 30
|
83 |
moves = null
|
84 |
+
scorer = {"@scorers":"spacy.parser_scorer.v1"}
|
85 |
update_with_oracle_cut_size = 100
|
86 |
|
87 |
[components.parser.model]
|
|
|
100 |
|
101 |
[components.senter]
|
102 |
factory = "senter"
|
103 |
+
overwrite = false
|
104 |
+
scorer = {"@scorers":"spacy.senter_scorer.v1"}
|
105 |
|
106 |
[components.senter.model]
|
107 |
@architectures = "spacy.Tagger.v1"
|
|
|
148 |
|
149 |
[corpora.dev]
|
150 |
@readers = "spacy.Corpus.v1"
|
151 |
+
path = ${paths.dev}
|
|
|
|
|
152 |
gold_preproc = false
|
153 |
+
max_length = 0
|
154 |
+
limit = 0
|
155 |
augmenter = null
|
156 |
|
157 |
[corpora.train]
|
158 |
@readers = "spacy.Corpus.v1"
|
159 |
+
path = ${paths.train}
|
|
|
160 |
gold_preproc = false
|
161 |
+
max_length = 0
|
162 |
limit = 0
|
163 |
augmenter = null
|
164 |
|
|
|
191 |
t = 0.0
|
192 |
|
193 |
[training.logger]
|
194 |
+
@loggers = "spacy.ConsoleLogger.v1"
|
195 |
+
progress_bar = false
|
|
|
196 |
|
197 |
[training.optimizer]
|
198 |
@optimizers = "Adam.v1"
|
|
|
206 |
learn_rate = 0.001
|
207 |
|
208 |
[training.score_weights]
|
209 |
+
pos_acc = 0.11
|
210 |
+
morph_micro_f = 0.33
|
211 |
+
morph_per_feat = null
|
212 |
dep_uas = 0.0
|
213 |
+
dep_las = 0.21
|
214 |
dep_las_per_type = null
|
215 |
sents_p = null
|
216 |
sents_r = null
|
217 |
+
sents_f = 0.03
|
218 |
+
ents_f = 0.21
|
219 |
ents_p = 0.0
|
220 |
ents_r = 0.0
|
221 |
ents_per_type = null
|
222 |
+
morph_acc = 0.11
|
223 |
+
speed = 0.0
|
224 |
|
225 |
[pretraining]
|
226 |
|
227 |
[initialize]
|
228 |
+
vocab_data = null
|
229 |
vectors = ${paths.vectors}
|
230 |
init_tok2vec = ${paths.init_tok2vec}
|
231 |
before_init = null
|
|
|
233 |
|
234 |
[initialize.components]
|
235 |
|
236 |
+
[initialize.components.morphologizer]
|
237 |
+
|
238 |
+
[initialize.components.morphologizer.labels]
|
239 |
+
@readers = "spacy.read_labels.v1"
|
240 |
+
path = "corpus/labels/morphologizer.json"
|
241 |
+
require = false
|
242 |
+
|
243 |
[initialize.components.ner]
|
244 |
|
245 |
[initialize.components.ner.labels]
|
ja_core_news_md-any-py3-none-any.whl
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
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|
3 |
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size
|
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|
1 |
version https://git-lfs.github.com/spec/v1
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oid sha256:c851e760a3b18f48359d9c52828ced1d1bf2560063d8fcdfc161203e3eaf35eb
|
3 |
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size 43045518
|
meta.json
CHANGED
@@ -1,14 +1,14 @@
|
|
1 |
{
|
2 |
"lang":"ja",
|
3 |
"name":"core_news_md",
|
4 |
-
"version":"3.
|
5 |
-
"description":"Japanese pipeline optimized for CPU. Components: tok2vec, parser, senter, ner, attribute_ruler.",
|
6 |
"author":"Explosion",
|
7 |
"email":"contact@explosion.ai",
|
8 |
"url":"https://explosion.ai",
|
9 |
"license":"CC BY-SA 4.0",
|
10 |
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"spacy_version":">=3.
|
11 |
-
"spacy_git_version":"
|
12 |
"vectors":{
|
13 |
"width":300,
|
14 |
"vectors":20000,
|
@@ -18,6 +18,27 @@
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|
18 |
"labels":{
|
19 |
"tok2vec":[
|
20 |
|
|
|
|
|
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|
21 |
],
|
22 |
"parser":[
|
23 |
"ROOT",
|
@@ -78,12 +99,14 @@
|
|
78 |
},
|
79 |
"pipeline":[
|
80 |
"tok2vec",
|
|
|
81 |
"parser",
|
82 |
"attribute_ruler",
|
83 |
"ner"
|
84 |
],
|
85 |
"components":[
|
86 |
"tok2vec",
|
|
|
87 |
"parser",
|
88 |
"senter",
|
89 |
"attribute_ruler",
|
@@ -93,168 +116,184 @@
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|
93 |
"senter"
|
94 |
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|
95 |
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|
96 |
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97 |
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100 |
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102 |
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103 |
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|
104 |
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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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"p":0.6666666667,
|
@@ -262,44 +301,49 @@
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|
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|
263 |
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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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305 |
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|
@@ -307,36 +351,32 @@
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|
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|
308 |
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|
309 |
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|
310 |
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"p":
|
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|
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|
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|
314 |
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315 |
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|
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|
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|
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320 |
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|
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|
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325 |
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|
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|
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|
329 |
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}
|
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|
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|
331 |
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|
332 |
{
|
333 |
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"name":"UD Japanese GSD v2.
|
334 |
"url":"https://github.com/UniversalDependencies/UD_Japanese-GSD",
|
335 |
"license":"CC BY-SA 4.0",
|
336 |
"author":"Omura, Mai; Miyao, Yusuke; Kanayama, Hiroshi; Matsuda, Hiroshi; Wakasa, Aya; Yamashita, Kayo; Asahara, Masayuki; Tanaka, Takaaki; Murawaki, Yugo; Matsumoto, Yuji; Mori, Shinsuke; Uematsu, Sumire; McDonald, Ryan; Nivre, Joakim; Zeman, Daniel"
|
337 |
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|
338 |
{
|
339 |
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"name":"UD Japanese GSD v2.
|
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"url":"https://github.com/megagonlabs/UD_Japanese-GSD",
|
341 |
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|
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"author":"Megagon Labs Tokyo"
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|
|
1 |
{
|
2 |
"lang":"ja",
|
3 |
"name":"core_news_md",
|
4 |
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"version":"3.2.0",
|
5 |
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"description":"Japanese pipeline optimized for CPU. Components: tok2vec, morphologizer, parser, senter, ner, attribute_ruler.",
|
6 |
"author":"Explosion",
|
7 |
"email":"contact@explosion.ai",
|
8 |
"url":"https://explosion.ai",
|
9 |
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|
10 |
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"spacy_version":">=3.2.0,<3.3.0",
|
11 |
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"spacy_git_version":"bb26550e2",
|
12 |
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|
13 |
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|
14 |
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|
|
18 |
"labels":{
|
19 |
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|
20 |
|
21 |
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],
|
22 |
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"morphologizer":[
|
23 |
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"POS=NOUN",
|
24 |
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|
25 |
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|
26 |
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|
27 |
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|
28 |
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|
29 |
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"POS=PART",
|
30 |
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"POS=DET",
|
31 |
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"POS=NUM",
|
32 |
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"POS=ADV",
|
33 |
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"POS=PRON",
|
34 |
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"POS=ADJ",
|
35 |
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"POS=PROPN",
|
36 |
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|
37 |
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"POS=SYM",
|
38 |
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|
39 |
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|
40 |
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"POS=INTJ",
|
41 |
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"POS=SCONJ|Polarity=Neg"
|
42 |
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|
43 |
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|
44 |
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|
|
99 |
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|
100 |
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|
101 |
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|
102 |
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"morphologizer",
|
103 |
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|
104 |
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|
105 |
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|
106 |
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|
107 |
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|
108 |
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|
109 |
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"morphologizer",
|
110 |
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|
111 |
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|
112 |
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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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morphologizer/cfg
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{
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size 7749
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senter/cfg
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tok2vec/model
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vocab/strings.json
CHANGED
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vocab/vectors.cfg
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