AjayMukundS/Llama-2-7b-LTS-finetuned-v3
Summarization • Updated • 2 • 1
Judgement-Summary Pairs stringlengths 1.44k 967k |
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<s>[INST] Summarize the following judgement: Appeal No. LXVI of 1949.
Appeal from the High Court of judicature, Bombay, in a reference under section 66 of the Indian Income tax Act, 1022.
K.M. Munshi (N. P. Nathvani, with him), for the appel lant. ' M.C. Setalvad, Attorney General for India (H. J. Umrigar, with him), f... |
<s>[INST] Summarize the following judgement: Civil Appeal No.94 of 1949.
107 834 Appeal from a judgment and decree of the High Court of Judi cature at Patna in Appeal from Appellate Decree No. 97 of 1946 (Mannohar Lall and Mukherji JJ.) dated 23rd Decem ber, 1947, confirming the judgment of the District Judge of Puruli... |
<s>[INST] Summarize the following judgement: iminal Appeal No. 40 of 1951, 127 Appeal from the Judgment and Order dated the 1st June, 1951, of the High Court of Judicature in Assam (Thadani C.J. and Ram Labhaya J.,) in Criminal Reference No. I of 1951, arising out of Judgment and Order dated the 15th November, 1950, of... |
<s>[INST] Summarize the following judgement: Appeal No. 388 of 1960.
Appeal by special leave from the judgment and order dated February 3, 1959, of the Patna High Court in Election Appeal No. 10 of 1958.
section P. Varma, for the appellant.
L. K. Jha and D. Govardhan, for respondent No. 1.
L. K. Jha and K. K. Sinha, fo... |
<s>[INST] Summarize the following judgement: Appeal No. 198 of 1954.
Appeal from the judgment and order dated October 16, 1952, of the former Nagpur High Court in Misc. Petn.; No. 1231 of 1951.
M. section K. Sastri, for the appellant.
H. L. Khaskalam, B. K. B. Naidu and I. N. Shroff, for the respondent.
64 502 1960.
No... |
<s>[INST] Summarize the following judgement: Appeals Nos. 155 to 160 of 1956.
Appeals from the judgments and orders of the Bombay High Court dated July 6, 1954, in Special Civil Applications Nos. 393, 395, 409 and 632 of 1954; July 19, 1954, in Special Civil Application No. 1205 of 1954; and July 30, 1954, in Special C... |
<s>[INST] Summarize the following judgement: iminal Appeal No. 68 of 1958.
Appeal by special leave from the judgment and order dated July 11, 1957, of the Allahabad High Court (Lucknow Bench), Lucknow, in Criminal Appeal No. 515 of 1955, arising out of the judgment and order dated October 31, 1955, of the Special Judge... |
<s>[INST] Summarize the following judgement: minal Appeal No. 124 of 1959.
Appeal by special leave from the judgment and order dated June 19 and 20, 1959, of the former Bombay High Court in Criminal Appeal No. 411 of 1959 arising out of the judgment and order dated March 17, 1959, of the Presidency Magistrate XX Court,... |
<s>[INST] Summarize the following judgement: Appeal No. 198 of 1954.
Appeal from the judgment and order dated October 16, 1952, of the former Nagpur High Court in Misc.
; No. 1231 of 1951.
M. section K. Sastri, for the appellant.
H. L. Khaskalam, B. K. B. Naidu and I. N. Shroff, for the respondent.
64 502 1960.
Novembe... |
<s>[INST] Summarize the following judgement: Appeal No. 285 of 1959.
Appeal by Special Leave from the Judgment and Decree dated the 13th July, 1956, of the Patna High Court in M. J. C. No. 404 of 1954.
M. C. Setalvad, Attorney General for India and section P. Varma, for the Appellants.
A. V. Viswanatha Sastri, Suresh A... |
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Reformatted Legal Text Summarization Dataset
Overview
This dataset is a restructured version of a Legal Text Summarization dataset, specifically filtered to include only entries from the IN-Abs dataset. The dataset consists of pairs of legal judgements and their corresponding summaries. Each judgement-summary pair is formatted into an Instruction-Prompt style format suitable for training language models for tasks like Summarization and Legal Text Analysis.
Dataset Structure
- Column Name:
Judgement-Summary Pairs - Format: The dataset contains one column named "Judgement-Summary Pairs", which holds the formatted instruction-prompt pairs. Each entry is a structured pair of a legal judgement and its corresponding summary.
Example of an Entry:
<s>[INST] Summarize the following judgement: [Judgement Text] [/INST] [Summary Text] </s>
Where: [Judgement Text] is the original legal judgement text. [Summary Text] is the summary of the judgement.
Sample Entry:
<s>[INST] Summarize the following judgement: The court finds that the defendant was not responsible for the damages caused as there was insufficient evidence to support the claims made by the plaintiff. [/INST] The court ruled in favor of the defendant due to lack of evidence. </s>
Data Preparation Process:
The dataset was prepared using the following steps:
- Filtering: The dataset was filtered to include only entries from the IN-Abs dataset.
- Transformation: Each judgement and its corresponding summary were formatted into instruction-prompt pairs using the following template:
<s>[INST] Summarize the following judgement: {judgement_text} [/INST] {summary_text} </s>
- Column Removal: All columns except the newly created "Judgement-Summary Pairs" were removed to streamline the dataset for usage.
Usage
The reformatted dataset is suitable for training language models on legal text summarization tasks. Here’s how you can use it:
- Load the Dataset: Use a data loading library like datasets or pandas to read the dataset.
- Training a Model: You can train a model using the instruction-prompt pairs provided in the dataset. Each pair serves as an input-output example for supervised learning, particularly in the fields of natural language processing (NLP) and legal AI.
- Fine-tuning Existing Models: Fine-tune pre-trained models such as GPT, BERT, or LLaMA on this dataset to adapt them for legal text summarization tasks.
License
The dataset is made available for educational and research purposes. Please ensure that you have the appropriate permissions and rights to use the original data before utilizing this reformatted version.
Acknowledgements
The dataset preparation and transformation were inspired by the need to improve legal text summarization and the creation of structured datasets for NLP tasks. Special thanks to the original data providers and contributors to legal text summarization research
Contact
For questions or further information, please contact Ajay Mukund S at ajaymukund1998@gmail.com.
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