The legal industry is built around documents as they provide evidence and reduce doubt in the court. Due to the large volume of documentation in the legal industry, the processing and summarization of these documents is important to a number of individuals. We were able to create a user interface that allows for the input of documents and makes use of the algorithm we created to output a summary of the document which can be copied by the user.
We analyze the accuracy of various NLP algorithms in providing text summarization and fine-tune a particular model on a dataset to provide accurate text summaries of legal documents. The legal industry is built around documents as they provide evidence and reduce doubt in the court. Due to the large volume of documentation in the legal industry, the processing and summarization of these documents is important to a number of individuals. For example, lawyers, clients and professionals may need access to summaries of the documents for reference to similar cases. In this paper, we have developed an algorithm that trains the T5 model on the legal domain in order to create more accurate summaries of legal documents. We were able to create a user interface that allows for the input of documents and makes use of the algorithm we created to output a summary of the document which can be copied by the user.
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