Error Span

Error Span Annotation (ESA) is a method for evaluating the quality of machine translations and other text outputs by identifying and classifying specific erroneous segments within the text, rather than relying solely on overall scores. Current research focuses on improving the efficiency and accuracy of ESA through AI-assisted annotation, leveraging machine learning models to pre-identify potential errors and reduce human workload. This approach offers a more granular and informative assessment than traditional methods, leading to more effective feedback for improving machine translation systems and other text generation tasks, such as writing assistance.