Implementing Commonsense Reasoning Via Semantic Skeletons for Answering Complex Questions
نویسنده
چکیده
We build the knowledge representation machinery for answering complex questions in poorly formalized and logically complex domains. Answers are annotated with deductively linked logical expressions (semantic skeletons), which are to be matched with formal representations for questions. Technique of semantic skeletons is a further development of our semantic headerbased approach to question answering. The question-answering technique has been implemented for the financial and legal domains, which are rather sophisticated on one hand and requires fairly precise answers on the other hand.
منابع مشابه
Building a Repository of Background Knowledge Using Semantic Skeletons
We build the knowledge representation machinery for answering complex questions in poorly formalized and logically complex domains. Answers are annotated with deductively linked logical expressions (semantic skeletons), which are to be matched with formal representations for questions. Technique of semantic skeletons is a further development of our semantic headerbased approach to question answ...
متن کاملExplicit Reasoning over End-to-End Neural Architectures for Visual Question Answering
Many vision and language tasks require commonsense reasoning beyond data-driven image and natural language processing. Here we adopt Visual Question Answering (VQA) as an example task, where a system is expected to answer a question in natural language about an image. Current state-ofthe-art systems attempted to solve the task using deep neural architectures and achieved promising performance. ...
متن کاملA Distributional Semantics Approach for Selective Reasoning on Commonsense Graph Knowledge Bases
Tasks such as question answering and semantic search are dependent on the ability of querying & reasoning over large-scale commonsense knowledge bases (KBs). However, dealing with commonsense data demands coping with problems such as the increase in schema complexity, semantic inconsistency, incompleteness and scalability. This paper proposes a selective graph navigation mechanism based on a di...
متن کاملExplicit Reasoning over End-to-End Neural Architectures
Many vision and language tasks require commonsense reasoning beyond data-driven image and natural language processing. Here we adopt Visual Question Answering (VQA) as an example task, where a system is expected to answer a question in natural language about an image. Current state-ofthe-art systems attempted to solve the task using deep neural architectures and achieved promising performance. ...
متن کاملCommonsense Reasoning
In spite of the recent shift of interest of the computational linguistics community to statistical approaches to NLP, the role of commonsense reasoning in semantic and pragmatic processing remains strong. Traditionally, it has been the commonsense reasoning community, and, in particular, the nonmonotonic reasoning community, that have considered linguistic applications of reasoning; however, th...
متن کامل