Annotation Scheme

Annotation schemes are structured frameworks for labeling data, crucial for training machine learning models in various natural language processing tasks. Current research focuses on developing schemes for nuanced aspects of language, such as fine-grained genericity in noun phrases, complex argumentation structures, and specialized domains like fashion and legal contracts. These improved schemes, often coupled with supervised fine-tuned models or large language models, aim to enhance the accuracy and reliability of NLP applications by providing richer, more contextually aware training data. The resulting advancements have significant implications for improving the performance of various NLP systems and facilitating deeper linguistic analysis.