Entities, as the essential elements in relation extraction tasks, exhibit certain structure. In this work, we formulate such entity structure distinctive dependencies between mention pairs. We then propose SSAN, which incorporates these structural within standard self-attention mechanism and throughout overall encoding stage. Specifically, design two alternative transformation modules inside ea...

Introduction. We are motivated by the problem of learning rules from naturally available data sources such as natural language texts, web pages, and medical databases. At first, learning rules from natural sources like the web seems to consist of extracting specific facts followed by data mining of rules. Unfortunately, however, there are two major obstacles to fully realizing the dream of unli...

Health mention classification (HMC) involves the of an input text as health or not. Figurative and non-health disease words makes task challenging. Learning context is key to this problem. The idea learn word representation by its surrounding utilize emojis in help improve results. In paper, we using adversarial training that acts a regularizer during fine-tuning model. We generate examples per...

thanks to the development of the concept of metadiscourse, it is now widely acknowledged that academic/scientific writing is not only concerned with communicating purely propositional meanings: what is communicated through academic/scientific communication is seen to be intertwined with the negotiation of social and interpersonal meanings. while a large number of so called metadiscoursal resour...