changing 'label' to 'sub_law_area'

README.md

@@ -4,9 +4,9 @@ license: cc-by-sa-4.0
 # Swiss Law Area Prediction
 
 ## Introduction
-The main subset contains cases to be classified into the four main areas of law: Public, Civil, Criminal and Social
+The dataset contains cases to be classified into the four main areas of law: Public, Civil, Criminal and Social
 
-A portion of the cases can be classified further into sub-areas:
+These can be classified further into sub-areas:
 ```
 "public": ['Tax', 'Urban Planning and Environmental', 'Expropriation', 'Public Administration', 'Other Fiscal'],
 "civil": ['Rental and Lease', 'Employment Contract', 'Bankruptcy', 'Family', 'Competition and Antitrust', 'Intellectual Property'],
@@ -15,47 +15,22 @@ A portion of the cases can be classified further into sub-areas:
 
 
 ## Size
-### Main dataset
-* train: 194'768
-* validation: 36'882
-* test: 97'676
-
-### Sub-area dataset
 * train: 10'475
 * validation: 3194
 * test: 8587
 
 
 ## Load datasets
-Load the main dataset:
 ```python
 dataset = load_dataset("rcds/swiss_law_area_prediction")
 ```
-Load the dataset with the sub-areas:
-```python
-dataset = load_dataset("rcds/swiss_law_area_prediction", "sub_area")
-```
 
 ## Columns
-### Main dataset
-- decision_id: unique identifier for the decision
-- facts: facts section of the decision
-- considerations: considerations section of the decision
-- label: label of the decision (main area of law)
-- law_sub_area: sub area of law of the decision
-- language: language of the decision
-- year: year of the decision
-- court: court of the decision
-- chamber: chamber of the decision
-- canton: canton of the decision
-- region: region of the decision
-
-### Sub-area dataset
 - decision_id: unique identifier for the decision
 - facts: facts section of the decision
 - considerations: considerations section of the decision
 - law_area: label of the decision (main area of law)
-- label: sub area of law of the decision
+- law_sub_area: sub area of law of the decision
 - language: language of the decision
 - year: year of the decision
 - court: court of the decision

swiss_law_area_prediction.py

@@ -35,15 +35,12 @@ _LICENSE = ""
 # The HuggingFace Datasets library doesn't host the datasets but only points to the original files.
 # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
 _URLS = {
-    "main": "https://huggingface.co/datasets/rcds/law_area_prediction/resolve/main/data/areas/huggingface",
-    "sub": "https://huggingface.co/datasets/rcds/law_area_prediction/resolve/main/data/sub_areas/huggingface"
+    "main": "https://huggingface.co/datasets/rcds/law_area_prediction/resolve/main/data/sub_areas/huggingface"
 }
 
 def get_url(config_name):
     if config_name == "main":
         return _URLS["main"]
-    if config_name == "sub_area":
-        return _URLS["sub"]
 
 
 class LawAreaPrediction(datasets.GeneratorBasedBuilder):
@@ -63,8 +60,7 @@ class LawAreaPrediction(datasets.GeneratorBasedBuilder):
     # data = datasets.load_dataset('my_dataset', 'first_domain')
     # data = datasets.load_dataset('my_dataset', 'second_domain')
     BUILDER_CONFIGS = [
-        datasets.BuilderConfig(name="main", version=VERSION, description="This part of my dataset covers the whole dataset"),
-        datasets.BuilderConfig(name="sub_area", version=VERSION, description="This dataset is for predicting sub law areas"),
+        datasets.BuilderConfig(name="main", version=VERSION, description="Whole dataset"),
     ]
 
     DEFAULT_CONFIG_NAME = "main"  # It's not mandatory to have a default configuration. Just use one if it make sense.
@@ -76,7 +72,7 @@ class LawAreaPrediction(datasets.GeneratorBasedBuilder):
                     "decision_id": datasets.Value("string"),
                     "facts": datasets.Value("string"),
                     "considerations": datasets.Value("string"),
-                    "label": datasets.Value("string"),
+                    "law_area": datasets.Value("string"),
                     "law_sub_area": datasets.Value("string"),
                     "language": datasets.Value("string"),
                     "year": datasets.Value("int32"),
@@ -88,22 +84,6 @@ class LawAreaPrediction(datasets.GeneratorBasedBuilder):
                     # These are the features of your dataset like images, labels ...
                 }
             )
-        if self.config.name != "main":  # for law sub area prediction
-            features = datasets.Features(
-                {
-                    "decision_id": datasets.Value("string"),
-                    "facts": datasets.Value("string"),
-                    "considerations": datasets.Value("string"),
-                    "law_area": datasets.Value("string"),
-                    "label": datasets.Value("string"),
-                    "language": datasets.Value("string"),
-                    "year": datasets.Value("int32"),
-                    "court": datasets.Value("string"),
-                    "chamber": datasets.Value("string"),
-                    "canton": datasets.Value("string"),
-                    "region": datasets.Value("string")
-                }
-            )
         return datasets.DatasetInfo(
             # This is the description that will appear on the datasets page.
             description=_DESCRIPTION,
@@ -188,8 +168,8 @@ class LawAreaPrediction(datasets.GeneratorBasedBuilder):
                                 "decision_id": data["decision_id"],
                                 "facts": data["facts"],
                                 "considerations": data["considerations"],
-                                "label": data["label"],
-                                "law_sub_area": data["law_sub_area"],
+                                "law_area": data["law_area"],
+                                "law_sub_area": data["label"],
                                 "language": data["language"],
                                 "year": data["year"],
                                 "court": data["court"],
@@ -197,20 +177,6 @@ class LawAreaPrediction(datasets.GeneratorBasedBuilder):
                                 "canton": data["canton"],
                                 "region": data["region"]
                             }
-                        if self.config.name == "sub_area":
-                                yield id, {
-                                    "decision_id": data["decision_id"],
-                                    "facts": data["facts"],
-                                    "considerations": data["considerations"],
-                                    "law_area": data["law_area"],
-                                    "label": data["label"],
-                                    "language": data["language"],
-                                    "year": data["year"],
-                                    "court": data["court"],
-                                    "chamber": data["chamber"],
-                                    "canton": data["canton"],
-                                    "region": data["region"]
-                                }
         except lzma.LZMAError as e:
             print(split, e)
             if line_counter == 0: