Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Linguistic and semantic annotations are important features for text-based applications. Hover, achieving and maintaining a good quality of a set of annotations is known to be a complex task. Many ad hoc approaches have been developed to produce various types of annotations, while comparing those annotations to improve their quality is still rare. ,  propose a framework in which both linguistic and domain information can cooperate to reason with annotations. The underlying knowledge representation issues are carefully analyzed and solved by studying a higher order logic, which accounts for the cooperation of different sorts of knowledge. Our prototype implements this logic based on a reduction to classical description logics by preserving the semantics, allowing us to benefit from cutting-edge Semantic b reasoners. An application scenario shows interesting merits of this framework on reasoning with annotations of texts.
['Yue Ma', 'François Lévy', 'Sudeep Ghimire']
I am writing a research paper on a idea Reasoning with Annotations of Texts
[{"from": "human", "value": "I am writing a research paper on a idea Reasoning with Annotations of Texts"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Linguistic and semantic annotations are important features for text-based applications. Hover, achieving and maintaining a good quality of a set of annotations is known to be a complex task. Many ad hoc approaches have been developed to produce various types of annotations, while comparing those annotations to improve their quality is still rare. ,  propose a framework in which both linguistic and domain information can cooperate to reason with annotations. The underlying knowledge representation issues are carefully analyzed and solved by studying a higher order logic, which accounts for the cooperation of different sorts of knowledge. Our prototype implements this logic based on a reduction to classical description logics by preserving the semantics, allowing us to benefit from cutting-edge Semantic b reasoners. An application scenario shows interesting merits of this framework on reasoning with annotations of texts."}]