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Update README.md

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@@ -5,8 +5,6 @@ language_creators:
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  - found
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  language:
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  - he
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- license:
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- - other
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  multilinguality:
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  - monolingual
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  size_categories:
@@ -29,8 +27,8 @@ train-eval-index:
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  tokens: tokens
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  ner_tags: tags
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  metrics:
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- - type: seqeval
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- name: seqeval
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  ---
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@@ -38,17 +36,26 @@ train-eval-index:
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  **Disclaimer**: It's just a huggingface datasets convenient interface for research purpose which is fetching the original data from [github](https://github.com/OnlpLab/NEMO-Corpus). I'm not an author of this work.
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  ```python
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  from datasets import load_dataset
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  # the main corpus
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- ds = load_dataset('imvladikon/nemo_corpus')
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  for sample in ds["train"]:
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  print(sample)
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  # the nested corpus
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- ds = load_dataset('imvladikon/nemo_corpus', "nested")
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  ```
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  Getting classes and encoding/decoding could be done through these functions:
@@ -66,11 +73,10 @@ available fields (flat):
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  * "tokens"
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  * "raw_tags"
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  * "ner_tags"
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- * "spans"
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  Example of the one record for `flat`:
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  ```json
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- {'id': '0', 'tokens': ['"', 'ืชื”ื™ื”', 'ื ืงืžื”', 'ื•', 'ื‘ื’ื“ื•ืœ', '.'], 'sentence': '" ืชื”ื™ื” ื ืงืžื” ื• ื‘ื’ื“ื•ืœ .', 'raw_tags': ['O', 'O', 'O', 'O', 'O', 'O'], 'ner_tags': [24, 24, 24, 24, 24, 24], 'spans': {'span': [], 'start': [], 'end': [], 'entity': [], 'start_char': [], 'end_char': []}}
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  ```
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  Example of the one record for `nested`:
 
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  - found
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  language:
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  - he
 
 
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  multilinguality:
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  - monolingual
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  size_categories:
 
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  tokens: tokens
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  ner_tags: tags
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  metrics:
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+ - type: seqeval
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+ name: seqeval
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  ---
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  **Disclaimer**: It's just a huggingface datasets convenient interface for research purpose which is fetching the original data from [github](https://github.com/OnlpLab/NEMO-Corpus). I'm not an author of this work.
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+ ## Config and Usage
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+
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+ Config:
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+ * flat_token - flatten tags
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+ * nested_token - nested tags
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+ * flat_morph - flatten tags with morphologically presegmentized tokens
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+ * nested_morph - nested tags with morphologically presegmentized tokens
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+
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+ Note: It seems that a couple of samples for the flat_token and nested_token are mistakenly presegmented, and as a result, these samples have white space in the token.
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  ```python
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  from datasets import load_dataset
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  # the main corpus
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+ ds = load_dataset('imvladikon/nemo_corpus', "flat_token")
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  for sample in ds["train"]:
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  print(sample)
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  # the nested corpus
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+ ds = load_dataset('imvladikon/nemo_corpus', "nested_morph")
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  ```
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  Getting classes and encoding/decoding could be done through these functions:
 
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  * "tokens"
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  * "raw_tags"
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  * "ner_tags"
 
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  Example of the one record for `flat`:
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  ```json
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+ {'id': '0', 'tokens': ['"', 'ืชื”ื™ื”', 'ื ืงืžื”', 'ื•', 'ื‘ื’ื“ื•ืœ', '.'], 'sentence': '" ืชื”ื™ื” ื ืงืžื” ื• ื‘ื’ื“ื•ืœ .', 'raw_tags': ['O', 'O', 'O', 'O', 'O', 'O'], 'ner_tags': [24, 24, 24, 24, 24, 24]}
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  ```
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  Example of the one record for `nested`: