Annotated Corpus

Annotated corpora are collections of text data meticulously labeled with linguistic or domain-specific information, serving as crucial training resources for natural language processing (NLP) models. Current research emphasizes the creation of such corpora for diverse domains, including cybersecurity, chemistry, law, and medicine, often employing large language models (LLMs) and recurrent neural networks (RNNs) like LSTMs for annotation and analysis. These resources are vital for advancing NLP capabilities in specialized fields, enabling improved information extraction, knowledge graph construction, and ultimately, more effective applications in various sectors.

Papers