In the legal domain, documents of various types are created in connection with a case. Some are transcripts prepared by court reporters, based on notes taken during the proceedings of a trial or deposition. For example, deposition transcripts capture the conversations between attorneys and deponents. These documents are mostly in the form of question-answer (QA) pairs. Summarizing the information contained in these documents is a challenge for attorneys and paralegals because of their length and form. Having automated methods to convert a QA pair into a canonical form could aid with the extraction of insights from depositions. These insights could be in the form of a short summary, a list of key facts, a set of answers to specific questions, or a similar result from text processing of these documents. In this paper, we describe methods using NLP and Deep Learning techniques to transform such QA pairs into a canonical form. The resulting transformed documents can be used for summarization and other downstream tasks.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com