| Lydia Lazib,Zhao Yanyan,Qin Bing,Liu Ting.[J].高技术通讯(英文),2017,23(2):191~197 |
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| Negation scope detection with a conditional random field model |
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| DOI：10.3772/j.issn.1006-6748.2017.02.011 |
| 中文关键词: |
| 英文关键词: negation detection, negation cue detection, negation scope detection, natural language processing |
| 基金项目: |
| Author Name | Affiliation | | Lydia Lazib | | | Zhao Yanyan | | | Qin Bing | | | Liu Ting | |
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| 中文摘要: |
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| 英文摘要: |
| 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. |
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