Datasets:
Update README.md
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README.md
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@@ -93,17 +93,256 @@ The text in the dataset is English.
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## Dataset Structure
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### Data Instances
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```json
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```
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### Data Fields
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- `text`: `str` of the text
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@@ -112,15 +351,22 @@ The text in the dataset is English.
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- `panel_start`: `list` of `strings` for IOB2 tags `["O", "B-PANEL_START"]`
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### Data Splits
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## Dataset Creation
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### Curation Rationale
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The dataset was built to train models for the automatic extraction of a knowledge graph based from the scientific literature. The dataset can be used to train character-based models for text segmentation and named entity recognition.
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## Dataset Structure
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### Data Instances
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```json
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{'text': '(E) Quantification of the number of cells without γ-Tubulin at centrosomes (γ-Tub -) in pachytene and diplotene spermatocytes in control, Plk1(∆/∆) and BI2536-treated spermatocytes. Data represent average of two biological replicates per condition. ',
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'labels': [0,
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0]}
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```
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### Data Fields
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- `text`: `str` of the text
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- `panel_start`: `list` of `strings` for IOB2 tags `["O", "B-PANEL_START"]`
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### Data Splits
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```python
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DatasetDict({
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train: Dataset({
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features: ['text', 'labels'],
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num_rows: 66085
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})
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test: Dataset({
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features: ['text', 'labels'],
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num_rows: 8225
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})
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validation: Dataset({
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features: ['text', 'labels'],
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num_rows: 7948
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})
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})
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```
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## Dataset Creation
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371 |
### Curation Rationale
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372 |
The dataset was built to train models for the automatic extraction of a knowledge graph based from the scientific literature. The dataset can be used to train character-based models for text segmentation and named entity recognition.
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