Identifying negation cues and their scope in a text is an important subtask of information extraction that can benefit other natural language processing tasks,including but not limited to medical data mining,relation ...Identifying negation cues and their scope in a text is an important subtask of information extraction that can benefit other natural language processing tasks,including but not limited to medical data mining,relation extraction,question answering and sentiment analysis.The tasks of negation cue and negation scope detection can be treated as sequence labelling problems.In this paper,a system is presented having two components:negation cue detection and negation scope detection.In the first phase,a conditional random field(CRF) model is trained to detect the negation cues using a lexicon of negation words and some lexical and contextual features.Then,another CRF model is trained to detect the scope of each negation cue identified in the first phase,using basic lexical and contextual features.These two models are trained and tested using the dataset distributed within the* Sem Shared Task 2012 on resolving the scope and focus of negation.Experimental results show that the system outperformed all the systems submitted to this shared task.展开更多
This paper deals with the scope of two types of English negation： the modal negation and the non-modal negation. It points out the possibility of ambiguity by reflecting the negative scope through word order in some ...This paper deals with the scope of two types of English negation： the modal negation and the non-modal negation. It points out the possibility of ambiguity by reflecting the negative scope through word order in some structures and discusses the special features of these structures.展开更多
基金Supported by the National High Technology Research and Development Programme of China(No.2015AA015407)the National Natural Science Foundation of China(No.61273321)the Specialized Research Fund for the Doctoral Program of Higher Education(No.20122302110039)
文摘Identifying negation cues and their scope in a text is an important subtask of information extraction that can benefit other natural language processing tasks,including but not limited to medical data mining,relation extraction,question answering and sentiment analysis.The tasks of negation cue and negation scope detection can be treated as sequence labelling problems.In this paper,a system is presented having two components:negation cue detection and negation scope detection.In the first phase,a conditional random field(CRF) model is trained to detect the negation cues using a lexicon of negation words and some lexical and contextual features.Then,another CRF model is trained to detect the scope of each negation cue identified in the first phase,using basic lexical and contextual features.These two models are trained and tested using the dataset distributed within the* Sem Shared Task 2012 on resolving the scope and focus of negation.Experimental results show that the system outperformed all the systems submitted to this shared task.
文摘This paper deals with the scope of two types of English negation： the modal negation and the non-modal negation. It points out the possibility of ambiguity by reflecting the negative scope through word order in some structures and discusses the special features of these structures.
