FlairNLP at SemEval-2023 Task 6b: Extraction of Legal Named Entities
  from Legal Texts using Contextual String Embeddings
Vinay N Ramesh Rohan Eswara
Indian court legal texts and processes are essential towards the integrity of
the judicial system and towards maintaining the social and political order of
the nation. Due to the increase in number of pending court cases, there is an
urgent need to develop tools to automate many of the legal processes with the
knowledge of artificial intelligence. In this paper, we employ knowledge
extraction techniques, specially the named entity extraction of legal entities
within court case judgements. We evaluate several state of the art
architectures in the realm of sequence labeling using models trained on a
curated dataset of legal texts. We observe that a Bi-LSTM model trained on
Flair Embeddings achieves the best results, and we also publish the BIO
formatted dataset as part of this paper.