Entity Enhancement

Entity enhancement focuses on improving the representation and utilization of entities within various machine learning tasks, aiming to boost performance by enriching contextual information and addressing data limitations. Current research explores techniques like embedding entity information into language models' hidden states, augmenting data with entity descriptions or visual features, and employing graph-based methods to capture relationships between entities. These advancements are significant for improving the accuracy and efficiency of tasks such as named entity recognition, relation extraction, and cross-lingual knowledge graph alignment, ultimately leading to more robust and effective AI systems.