基于框架语义扩展训练集的有监督事件检测方法
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摘要
事件检测是信息抽取领域的一个重要研究方向,目前的事件检测方法往往受限于数据稀疏、语料例句分布不平衡和歧义问题。该文研究发现框架语义知识库FrameNet(FN)含有丰富的已标注框架的语料,并且FN中定义的框架和事件检测中定义的事件具有极其相似的结构。框架由词法单元和一组框架元素组成,可与事件中的触发词和论元形成对应关系;而且,FN中的许多框架实际上也能表达某些事件。因此,该文利用这一相似性构建事件类型与框架类型的映射关系,从而选取FN中合适的例句作为事件检测的扩充语料,以此来优化事件检测性能。实验结果显示,针对触发词识别任务和事件类型识别任务,该文提出的框架语义辅助方法取得了较好的效果。
Event detection is an important research issue in the field of information extraction.The current methods of event detection generally suffer from data sparseness,imbalanced distribution and ambiguity.This paper proposes to construct the correspondence between event types and frames in FrameNet(FN),so as to get additional samples to train the supervised detection models.It is revealed that FN consists of richer examples of events which have been annotated with the tags of frame semantics.In addition,the frame defined in FN shares high similarity with that in ACE:e.g.the lexical units and a set of frame elements inherently correspond to the event triggers and arguments in the ACE corpus,and many frames in FN can represent certain types of events.Experimental results show that the proposed method performs well both in trigger identification and event type recognition.
Event detection is an important research issue in the field of information extraction.The current methods of event detection generally suffer from data sparseness,imbalanced distribution and ambiguity.This paper proposes to construct the correspondence between event types and frames in FrameNet(FN),so as to get additional samples to train the supervised detection models.It is revealed that FN consists of richer examples of events which have been annotated with the tags of frame semantics.In addition,the frame defined in FN shares high similarity with that in ACE:e.g.the lexical units and a set of frame elements inherently correspond to the event triggers and arguments in the ACE corpus,and many frames in FN can represent certain types of events.Experimental results show that the proposed method performs well both in trigger identification and event type recognition.
引文
[1]David Ahn.The stages of event extraction[C]//Proceedings of the Workshop on Annotating and Reasoning about Time and Event,Sydney,Australia,2006:1-8.
[2]杨雪蓉,洪宇,马彬,等.基于触发词和实体推理的事件关系识别方法[J].中文信息学报,2014,28(2):100-108.
[3]Prashant Gupta,Heng Ji.Predicting unknown time arguments based on cross-event propagation[C]//Proceedings of the ACL-IJCNLP 2009 Conference Short Papers,Suntec,Singapore,2009:369-372.
[4]Thien Huu Nguyen,Kyunghyun Cho,Ralph Grishman.Joint event extraction via recurrent neural networks[C]//Proceedings of the 2016Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2016:300-309.
[5]姜吉发.一种事件信息抽取模式获取方法[J].计算机工程,2005,31(15):96-98.
[6]Charles J.Fillmore.Frame semantics and the nature of language[C]//Annals of the New York Academy of Sciences:Conference on the Origin and Development of Language and Speech,New York,1976:20-32.
[7]Qi Li,Heng Ji,Liang Huang.Joint event extraction via structured prediction with global features[C]//Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics,Sofia,Bulgaria,2013:73-82.
[8]Thien Huu Nguyen,Ralph Grishman.Event detection and domain adaptation with convolutional neural networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the7th International Joint Conference on Natural Language Processing,Beijng,China,2015:365-371.
[9]Yubo Chen,Liheng Xu,Kang Liu,et al.Event extraction via dynamic multi-pooling convolutional neural networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing,Beijing,China,2015:167-176.
[10]Duyu Tang,Bing Qin,Ting Liu.Document modeling with gated recurrent neural network for sentiment classification[C]//Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing,Lisbon,Portugal,2015:1422-1432.
[11]Xiaocheng Feng,Lifu Huang,Duyu Tang,et al.Alanguage-independent neural network for event detection[J].Science China Information Sciences,2018,61(9):092106.
[12]Shulin Liu,Yubo Chen,Kang Liu,et al.Exploiting argument information to improve event detection via supervised attention mechanisms[C]//Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics,Vancouver,Canada,2017:1789-1798.
[13]Heng Ji,Ralph Grishman.Refining event extraction through cross-document inference[C]//Proceedings of ACL-08:HLT,2008:254-262.
[14]Yu Hong,Jianfeng Zhang and Bin Ma.Using crossentity inference to improve event extraction[C]//Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics,Protland,USA,2011:1127-1136.
[15]陈亚东,洪宇,王潇斌,等.利用框架语义知识优化事件抽取.[J].中文信息学报,2015,29(3):117-125.
[16]Shulin Liu,Yubo Chen,Shizhu He,et al.Leveraging framenet to improve automatic event detection[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics,Berlin,Germany,2016:2134-2143.
[17]Yubo Chen,Shulin Liu,Xiang Zhang,et al.Automatically labeled data generation for large scale event extraction[C]//Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics,Vancouver,Canada,2017:409-419.
[18]Srini Narayanan,Sanda Harabagiu.Question answering based on semantic structures[C]//Proceedings of the 20th International Conference on Computational Linguistics.Association for Computational Linguistics,2004:693.
[19]Dan Shen,Mirella Lapata.Using semantic roles to improve question answering[C]//Proceedings of the2007Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning[C]//Proceedings of the 2007Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning,2007:12-21.
[20]Sebastian Padóand Mirella Lapata.Cross-linguistic projection of role-semantic information[C]//Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing.Association for Computational Linguistics,2005:859-866.
[21]Aljoscha Burchardt,Marco Pennacchiotti,Stefan Thater,et al.Assessing the impact of frame semantics on textual entailment[J].Natural Language Engineering,2009,15(4):527-550.
[22]George Doddington.The automatic content extraction program-tasks,data,and evaluation[C]//Proceedings of the 4th International Conference on Language Resources and Evaluation,2004:837-840.
[23]Evangelia Spiliopoulou,Eduard Hovy,Teruko Mitamura T.Event detection using frame-semantic parser[C]//Proceedings of the Events and Stories in the News Workshop,Vancouver,Canada,2017:15-20.
[24]Sanjeev Arora,Yingyu Liang,Tengyu Ma.A simple but tough-to-beat baseline for sentence embeddings[C]//Proceedings of International Conference on Learning Representation,2016.
[25]Pengfei Liu,Xipeng Qiu,Jifan Chen,et al.Deep fusion LSTMs for text semantic matching[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics,Berlin,Germany.2016:1034-1043.
[26]Zhouhan Lin,Minwei Feng,Cicero Nogueira dos Santos,et al.A structured self-attentive sentence embedding[J].arXiv preprint arXiv:1703.03130,2017.
[27]Mike Schuster,Kuldip K Paliwal.Bidirectional recurrent neural networks[J].IEEE Transactions on Signal Processing,1997,45(11):2673-2681.
[28]Matthew DZeiler.Adadelta:An adaptive learning rate method[J].arXiv preprint arXiv:1212.5701,2012.
[29]Nitish Srivastava,Geoffrey Hinton,Alex Krizhevsky,et al.Dropout:a simple way to prevent neural networks from overfitting[J].The Journal of Machine Learning Research,2014,15(1):1929-1958.
[30]Tomas Mikolov,Wen-tau Yih,Geoffrey Zweig.Linguistic regularities in continuous space word representations[C]//Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2013:746-751.
[31]Alex Judea,Michael Strube.Event extraction as frame-semantic parsing[C]//Proceedings of the 4th Joint Conference on Lexical and Computational Semantics,Denver,Colorado,2015:159-164.
[32]Shulin Liu,Kang Liu,Shizhu He,et al.A probabilistic soft logic based approach to exploiting latent and global information in event classification[C]//Proceedings of the 13th AAAI Conference on Artificial Intelligence,2016.
(1)https://framenet2.icsi.berkeley.edu
(1)http://www.ark.cs.cmu.edu/SEMAFOR/
(1)http://mallet.cs.umass.edu/
(1)http://mallet.cs.umass.edu/
[2]杨雪蓉,洪宇,马彬,等.基于触发词和实体推理的事件关系识别方法[J].中文信息学报,2014,28(2):100-108.
[3]Prashant Gupta,Heng Ji.Predicting unknown time arguments based on cross-event propagation[C]//Proceedings of the ACL-IJCNLP 2009 Conference Short Papers,Suntec,Singapore,2009:369-372.
[4]Thien Huu Nguyen,Kyunghyun Cho,Ralph Grishman.Joint event extraction via recurrent neural networks[C]//Proceedings of the 2016Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2016:300-309.
[5]姜吉发.一种事件信息抽取模式获取方法[J].计算机工程,2005,31(15):96-98.
[6]Charles J.Fillmore.Frame semantics and the nature of language[C]//Annals of the New York Academy of Sciences:Conference on the Origin and Development of Language and Speech,New York,1976:20-32.
[7]Qi Li,Heng Ji,Liang Huang.Joint event extraction via structured prediction with global features[C]//Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics,Sofia,Bulgaria,2013:73-82.
[8]Thien Huu Nguyen,Ralph Grishman.Event detection and domain adaptation with convolutional neural networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the7th International Joint Conference on Natural Language Processing,Beijng,China,2015:365-371.
[9]Yubo Chen,Liheng Xu,Kang Liu,et al.Event extraction via dynamic multi-pooling convolutional neural networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing,Beijing,China,2015:167-176.
[10]Duyu Tang,Bing Qin,Ting Liu.Document modeling with gated recurrent neural network for sentiment classification[C]//Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing,Lisbon,Portugal,2015:1422-1432.
[11]Xiaocheng Feng,Lifu Huang,Duyu Tang,et al.Alanguage-independent neural network for event detection[J].Science China Information Sciences,2018,61(9):092106.
[12]Shulin Liu,Yubo Chen,Kang Liu,et al.Exploiting argument information to improve event detection via supervised attention mechanisms[C]//Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics,Vancouver,Canada,2017:1789-1798.
[13]Heng Ji,Ralph Grishman.Refining event extraction through cross-document inference[C]//Proceedings of ACL-08:HLT,2008:254-262.
[14]Yu Hong,Jianfeng Zhang and Bin Ma.Using crossentity inference to improve event extraction[C]//Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics,Protland,USA,2011:1127-1136.
[15]陈亚东,洪宇,王潇斌,等.利用框架语义知识优化事件抽取.[J].中文信息学报,2015,29(3):117-125.
[16]Shulin Liu,Yubo Chen,Shizhu He,et al.Leveraging framenet to improve automatic event detection[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics,Berlin,Germany,2016:2134-2143.
[17]Yubo Chen,Shulin Liu,Xiang Zhang,et al.Automatically labeled data generation for large scale event extraction[C]//Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics,Vancouver,Canada,2017:409-419.
[18]Srini Narayanan,Sanda Harabagiu.Question answering based on semantic structures[C]//Proceedings of the 20th International Conference on Computational Linguistics.Association for Computational Linguistics,2004:693.
[19]Dan Shen,Mirella Lapata.Using semantic roles to improve question answering[C]//Proceedings of the2007Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning[C]//Proceedings of the 2007Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning,2007:12-21.
[20]Sebastian Padóand Mirella Lapata.Cross-linguistic projection of role-semantic information[C]//Proceedings of the Conference on Human Language Technology and Empirical Methods in Natural Language Processing.Association for Computational Linguistics,2005:859-866.
[21]Aljoscha Burchardt,Marco Pennacchiotti,Stefan Thater,et al.Assessing the impact of frame semantics on textual entailment[J].Natural Language Engineering,2009,15(4):527-550.
[22]George Doddington.The automatic content extraction program-tasks,data,and evaluation[C]//Proceedings of the 4th International Conference on Language Resources and Evaluation,2004:837-840.
[23]Evangelia Spiliopoulou,Eduard Hovy,Teruko Mitamura T.Event detection using frame-semantic parser[C]//Proceedings of the Events and Stories in the News Workshop,Vancouver,Canada,2017:15-20.
[24]Sanjeev Arora,Yingyu Liang,Tengyu Ma.A simple but tough-to-beat baseline for sentence embeddings[C]//Proceedings of International Conference on Learning Representation,2016.
[25]Pengfei Liu,Xipeng Qiu,Jifan Chen,et al.Deep fusion LSTMs for text semantic matching[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics,Berlin,Germany.2016:1034-1043.
[26]Zhouhan Lin,Minwei Feng,Cicero Nogueira dos Santos,et al.A structured self-attentive sentence embedding[J].arXiv preprint arXiv:1703.03130,2017.
[27]Mike Schuster,Kuldip K Paliwal.Bidirectional recurrent neural networks[J].IEEE Transactions on Signal Processing,1997,45(11):2673-2681.
[28]Matthew DZeiler.Adadelta:An adaptive learning rate method[J].arXiv preprint arXiv:1212.5701,2012.
[29]Nitish Srivastava,Geoffrey Hinton,Alex Krizhevsky,et al.Dropout:a simple way to prevent neural networks from overfitting[J].The Journal of Machine Learning Research,2014,15(1):1929-1958.
[30]Tomas Mikolov,Wen-tau Yih,Geoffrey Zweig.Linguistic regularities in continuous space word representations[C]//Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2013:746-751.
[31]Alex Judea,Michael Strube.Event extraction as frame-semantic parsing[C]//Proceedings of the 4th Joint Conference on Lexical and Computational Semantics,Denver,Colorado,2015:159-164.
[32]Shulin Liu,Kang Liu,Shizhu He,et al.A probabilistic soft logic based approach to exploiting latent and global information in event classification[C]//Proceedings of the 13th AAAI Conference on Artificial Intelligence,2016.
(1)https://framenet2.icsi.berkeley.edu
(1)http://www.ark.cs.cmu.edu/SEMAFOR/
(1)http://mallet.cs.umass.edu/
(1)http://mallet.cs.umass.edu/