uploaded dataset files

README.md

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+# Dataset Card for LegalCaseDocumentSummarization
+
+## Table of Contents
+- [Table of Contents](#table-of-contents)
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [GitHub](https://github.com/Law-AI/summarization)
+- **Repository:** [Zenodo](https://zenodo.org/record/7152317#.Y69PkeKZODW)
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+[More Information Needed]
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+[More Information Needed]
+
+### Data Fields
+
+[More Information Needed]
+
+### Data Splits
+
+[More Information Needed]
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+[More Information Needed]
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]
+
+### Contributions
+
+Thanks to [@JoelNiklaus](https://github.com/JoelNiklaus) for adding this dataset.

original_dataset.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6141613c07eb5a16f0c3f0da0aec974bd218ce12d15035b9aba37dda3e7e1b96
+size 105247667

prepare_data.py

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+import pandas as pd
+
+import os
+from typing import Union
+
+import datasets
+from datasets import load_dataset
+
+
+
+def save_and_compress(dataset: Union[datasets.Dataset, pd.DataFrame], name: str, idx=None):
+    if idx:
+        path = f"{name}_{idx}.jsonl"
+    else:
+        path = f"{name}.jsonl"
+
+    print("Saving to", path)
+    dataset.to_json(path, force_ascii=False, orient='records', lines=True)
+
+    print("Compressing...")
+    os.system(f'xz -zkf -T0 {path}')  # -TO to use multithreading
+
+
+
+
+def get_dataset_column_from_text_folder(folder_path):
+    return load_dataset("text", data_dir=folder_path, sample_by="document", split='train').to_pandas()['text']
+
+
+for split in ["train", "test"]:
+    dfs = []
+    for dataset_name in ["IN-Abs", "UK-Abs", "IN-Ext"]:
+        if dataset_name == "IN-Ext" and split == "test":
+            continue
+        print(f"Processing {dataset_name} {split}")
+        path = f"original_dataset/{dataset_name}/{split}-data"
+
+        df = pd.DataFrame()
+        df['judgement'] = get_dataset_column_from_text_folder(f"{path}/judgement")
+        df['dataset_name'] = dataset_name
+
+        summary_full_path = f"{path}/summary"
+        if dataset_name == "UK-Abs":
+            if split == "test":
+                summary_full_path = f"{path}/summary/full"
+                for segment in ['background', 'judgement', 'reasons']:
+                    df[f'summary/{segment}'] = get_dataset_column_from_text_folder(
+                        f"{path}/summary/segment-wise/{segment}")
+        elif dataset_name == "IN-Ext":
+            summary_full_path = f"{path}/summary/full"
+            for annotator in ['A1', 'A2']:
+                for segment in ['facts', 'judgement']:  # errors when reading 'analysis' / 'argument' / 'statute'
+                    print(f"Processing {dataset_name} {split} {annotator} {segment}")
+                    df[f'summary/{annotator}/{segment}'] = get_dataset_column_from_text_folder(
+                        f"{path}/summary/segment-wise/{annotator}/{segment}")
+        df['summary/full'] = get_dataset_column_from_text_folder(summary_full_path)
+        dfs.append(df)
+    df = pd.concat(dfs)
+    save_and_compress(df, f"data/{split}")

test.jsonl.xz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:313dd03ac209312faa6ed75128d54878949bb8dad3fa8622c6936e6d5231dd41
+size 2323776

train.jsonl.xz

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+version https://git-lfs.github.com/spec/v1
+oid sha256:bc4714244b4cec524bfa56ee718f855d4d33e7a0fa3df595f9ce036ac5ac1ecc
+size 50589476