Identification of Rhetorical Roles of Sentences in Indian Legal Judgments

Paheli Bhattacharya, Shounak Paul, Kripabandhu Ghosh, Saptarshi Ghosh, Adam Wyner

Abstract:

. Automatically understanding the rhetorical roles of sentences in a le-
gal case judgement is an important problem to solve, since it can help in several
downstream tasks like summarization of legal judgments, legal search, and so on.
The task is challenging since legal case documents are usually not well-structured,
and these rhetorical roles may be subjective (as evident from variation of opinions
between legal experts). In this paper, we address this task for judgments from the
Supreme Court of India. We label sentences in 50 documents using multiple hu-
man annotators, and perform an extensive analysis of the human-assigned labels.
We also attempt automatic identification of the rhetorical roles of sentences. While
prior approaches towards this task used Conditional Random Fields over manu-
ally handcrafted features, we explore the use of deep neural models which do not
require hand-crafting of features. Experiments show that neural models perform
much better in this task than baseline methods which use handcrafted features.