Automatic Construction of a Polish Legal Dictionary with Mappings to Extra-Legal Terms Established via Word Embeddings

The primary objective of this research is finding correspondence between legal and extra-legal terms in Polish by employing unsupervised methods, such as statistics and word embeddings. We investigate the possibility to construct a legal dictionary automatically by employing statistical methods for identifying the legal terms (including multi-word entities) and then finding correspondence between these terms and extralegal terminology used by laymen, by employing word embeddings inducing algorithms. We compare two popular libraries word2vec and GloVe in a synthetic experiment showing the superiority of word2vec CBOW negative sampling variant in the described problem.