Enhancing Document Relevance Classification, Question Generation, and Passage Re-ranking using Semantic Triples

This research investigates using semantic triples as explicit features to enhance natural language tasks. The structural features and relations of triples hold latent semantic information and can be used to enrich language models. The findings indicate performance improvements in natural language tasks namely document relevance classification, question generation, and passage re-ranking.<p></p>