Update parquet files

README.md

@@ -1,122 +0,0 @@
-# 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.

test.jsonl.xz → joelito--legal_case_document_summarization/json-test.parquet

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+size 5669318

train.jsonl.xz → joelito--legal_case_document_summarization/json-train.parquet

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original_dataset.zip

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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
-
-        if dataset_name == "UK-Abs" and split == "test" or dataset_name == "IN-Ext":
-            summary_full_path = f"{path}/summary/full"
-        else:
-            summary_full_path = f"{path}/summary"
-        df['summary'] = get_dataset_column_from_text_folder(summary_full_path)
-        dfs.append(df)
-    df = pd.concat(dfs)
-    df = df.fillna("")  # NaNs can lead to huggingface not recognizing the feature type of the column
-    save_and_compress(df, f"data/{split}")