  Legal proceedings take plenty of time and also cost a lot. The lawyers have
to do a lot of work in order to identify the different sections of prior cases
and statutes. The paper tries to solve the first tasks in AILA2021 (Artificial
Intelligence for Legal Assistance) that will be held in FIRE2021 (Forum for
Information Retrieval Evaluation). The task is to semantically segment the
document into different assigned one of the 7 predefined labels or "rhetorical
roles." The paper uses BERT to obtain the sentence embeddings from a sentence,
and then a linear classifier is used to output the final prediction. The
experiments show that when more weightage is assigned to the class with the
highest frequency, the results are better than those when more weightage is
given to the class with a lower frequency. In task 1, the team legalNLP
obtained a F1 score of 0.22.
