Natural Language Processing for Legal Texts
Almost all law is expressed in natural language; therefore, natural language processing (NLP) is a key component of understanding and predicting law. Natural language processing converts unstructured text into a formal representation that computers can understand and analyze. This technology has already intersected with law, and is poised to experience rapid innovation and widespread adoption. There are three reasons for this: (1) the number of repositories of digitized machine-readable legal text data is growing; (2) advances in NLP tools are being driven by algorithmic and hardware improvements; and (3) there is great potential to dramatically improve the effectiveness of legal services due to inefficiencies in its current practice.
Almost all law is expressed in natural language; therefore, natural language processing (NLP) is a key component of understanding and predicting law. Natural language processing converts unstructured text into a formal representation that computers can understand and analyze. This technology has already intersected with law, and is poised to experience rapid innovation and widespread adoption. There are three reasons for this: (1) the number of repositories of digitized machine-readable legal text data is growing; (2) advances in NLP tools are being driven by algorithmic and hardware improvements; and (3) there is great potential to dramatically improve the effectiveness of legal services due to inefficiencies in its current practice.
