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Update README.md

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@@ -51,12 +51,32 @@ for sample in ds["train"]:
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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
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  ```
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  idx2label = dataset["train"].features["ner_tags"].feature.int2str
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  label2idx = dataset["train"].features["ner_tags"].feature.str2int
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  ```
 
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  ## Dataset Description
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  it's README.md of the [original repository](https://github.com/OnlpLab/NEMO-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:
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  ```
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  idx2label = dataset["train"].features["ner_tags"].feature.int2str
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  label2idx = dataset["train"].features["ner_tags"].feature.str2int
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  ```
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+ or just use raw_tags field.
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+ ## Fields
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+
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+ available fields (flat):
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+ * "id"
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+ * "sentence"
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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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+
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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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+
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+ Example of the one record for `nested`:
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+ ```json
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+ {'id': '0', 'tokens': ['"', 'ืชื”ื™ื”', 'ื ืงืžื”', 'ื•', 'ื‘ื’ื“ื•ืœ', '.'], 'ner_tags': [24, 24, 24, 24, 24, 24], 'ner_tags_2': [24, 24, 24, 24, 24, 24], 'ner_tags_3': [24, 24, 24, 24, 24, 24], 'ner_tags_4': [24, 24, 24, 24, 24, 24]}
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+ ```
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  ## Dataset Description
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  it's README.md of the [original repository](https://github.com/OnlpLab/NEMO-Corpus)