Update README.md

README.md

@@ -33,7 +33,12 @@ and the roles played on them by the biological entities.
 Each entity is linked to their correspondent ontology, allowing
 for entity disambiguation and NEL.
 
+## Dataset usage
 
+```python
+  from datasets import load_dataset
+  ds = load_dataset("EMBO/SourceData", "NER", version="1.0.0")
+```
 ## Dataset Description
 - **Homepage:** https://sourcedata.embo.org
 - **Repository:** https://github.com/source-data/soda-data
@@ -73,23 +78,46 @@ The text in the dataset is English.
 - `words`: `list` of `strings` text tokenized into words.
 - `panel_id`: ID of the panel to which the example belongs to in the SourceData database.
 - `label_ids`:
-  - `entity_types`: `list` of `strings` for the IOB2 tags for entity type; possible value in `["O", "I-SMALL_MOLECULE",  "B-SMALL_MOLECULE",  "I-GENEPROD", "B-GENEPROD", "I-SUBCELLULAR", "B-SUBCELLULAR", "I-CELL", "B-CELL", "I-TISSUE", "B-TISSUE", "I-ORGANISM", "B-ORGANISM", "I-EXP_ASSAY", "B-EXP_ASSAY"]`
-  - `geneprod_roles`: `list` of `strings` for the IOB2 tags for experimental roles; values in `["O", "I-CONTROLLED_VAR", "B-CONTROLLED_VAR", "I-MEASURED_VAR", "B-MEASURED_VAR"]`
-  - `boring`: `list` of `strings` for IOB2 tags for entities unrelated to causal design; values in `["O", "I-BORING", "B-BORING"]`
+  - `entity_types`: `list` of `strings` for the IOB2 tags for entity type; possible value in `["O", "I-SMALL_MOLECULE",  "B-SMALL_MOLECULE",  "I-GENEPROD", "B-GENEPROD", "I-SUBCELLULAR", "B-SUBCELLULAR", "I-CELL_LINE", "B-CELL_LINE", "I-CELL_TYPE", "B-CELL_TYPE", "I-TISSUE", "B-TISSUE", "I-ORGANISM", "B-ORGANISM", "I-EXP_ASSAY", "B-EXP_ASSAY"]`
+  - `roles`: `list` of `strings` for the IOB2 tags for experimental roles; values in `["O", "I-CONTROLLED_VAR", "B-CONTROLLED_VAR", "I-MEASURED_VAR", "B-MEASURED_VAR"]`
   - `panel_start`: `list` of `strings` for IOB2 tags `["O", "B-PANEL_START"]`  
-  - `small_mol_roles`: `list` of `strings` for IOB2 tags showing whether the entity is the variable being measured or the control variable `["O", "B-CONTROLLED_VAR", "I-CONTROLLED_VAR", "B-MEASURED_VAR", "I-MEASURED_VAR",]`
-
+  - `multi roles`: There are two different label sets. `labels` is like in `roles`. `is_category` tags `GENEPROD` and `SMALL_MOLECULE`.
 ### Data Splits
 
-- train:
-  - features: ['words', 'labels', 'tag_mask', 'panel_id'],
-  - num_rows: 50_198
-- validation:
-  - features: ['words', 'labels', 'tag_mask', 'panel_id'],
-  - num_rows: 5_946
-- test:
-  - features: ['words', 'labels', 'tag_mask', 'panel_id'],
-  - num_rows: 6_222
+* NER and ROLES
+```
+  DatasetDict({
+      train: Dataset({
+          features: ['words', 'labels', 'tag_mask', 'text'],
+          num_rows: 55250
+      })
+      test: Dataset({
+          features: ['words', 'labels', 'tag_mask', 'text'],
+          num_rows: 6844
+      })
+      validation: Dataset({
+          features: ['words', 'labels', 'tag_mask', 'text'],
+          num_rows: 7951
+      })
+  })
+```
+* PANELIZATION
+```
+  DatasetDict({
+      train: Dataset({
+          features: ['words', 'labels', 'tag_mask'],
+          num_rows: 14655
+      })
+      test: Dataset({
+          features: ['words', 'labels', 'tag_mask'],
+          num_rows: 1871
+      })
+      validation: Dataset({
+          features: ['words', 'labels', 'tag_mask'],
+          num_rows: 2088
+      })
+  })
+```
 
 ## Dataset Creation