Orphan Entity Allocation

Orphan entity allocation focuses on identifying and classifying unstructured data points—entities—that lack clear contextual categorization within larger datasets, such as resumes or knowledge graphs. Current research emphasizes leveraging knowledge graphs, language models (including both retrieval- and generation-based approaches), and advanced techniques like contrastive learning and self-regularization to improve the accuracy and efficiency of this allocation process. This work is significant for improving information extraction from unstructured data, impacting fields like talent acquisition, knowledge base construction, and software engineering by enabling more effective data analysis and automated processes.