{"type":"ScholarlyArticle","title":"Exploring Encoder-Decoder Model for Distant Supervised Relation Extraction","authors":[{"name":"Sen Su","slug":"sen-su","given":"Sen","family":"Su","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing 100876 , China"},{"name":"Ningning Jia","slug":"ningning-jia","given":"Ningning","family":"Jia","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing 100876 , China"},{"name":"Xiang Cheng","slug":"xiang-cheng","given":"Xiang","family":"Cheng","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing 100876 , China"},{"name":"Shuguang Zhu","slug":"shuguang-zhu","given":"Shuguang","family":"Zhu","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing 100876 , China"},{"name":"Ruiping Li","slug":"ruiping-li","given":"Ruiping","family":"Li","affiliation":"State Key Laboratory of Networking and Switching Technology , Beijing University of Posts and Telecommunications , Beijing 100876 , China"}],"abstract":"In this paper, we present an encoder-decoder model for distant supervised relation extraction. Given an entity pair and its sentence bag as input, in the encoder component, we employ the convolutional neural network to extract the features of the sentences in the sentence bag and merge them into a bag representation. In the decoder component, we utilize the long short-term memory network to model relation dependencies and predict the target relations in a sequential manner. In particular, to enable the sequential prediction of relations, we introduce a measure to quantify the amounts of information the relations take in their sentence bag, and use such information to determine the order of the relations of a sentence bag during model training. Moreover, we incorporate the attention mechanism into our model to dynamically adjust the bag representation to reduce the impact of sentences whose corresponding relations have been predicted. Extensive experiments on a popular dataset show that our model achieves significant improvement over state-of-the-art methods.","doi":"10.24963/ijcai.2018/610","url":"https://ijcai.org/proceedings/2018/610","pdf":"https://ijcai.org/proceedings/2018/0610.pdf","markdown":"https://ijcai.org/proceedings/2018/610.md","bibtex":"https://ijcai.org/proceedings/2018/bibtex/610","volume":{"slug":"2018","title":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2018","url":"https://ijcai.org/proceedings/2018/","year":2018,"location":"Stockholm","dates":"13-19 July 2018","editors":"Jérôme Lang","isbn":"978-0-9992411-2-7","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2018"},"section":"Natural Language Processing","track":"Main track","number":610,"pages":{"first":4389,"last":4395},"keywords":["Machine Learning: Deep Learning","Machine Learning: Multi-instance;Multi-label;Multi-view learning","Natural Language Processing: Information Extraction","Natural Language Processing: Knowledge Extraction","Machine Learning: Neural Networks"],"videos":[],"references":[{"position":1,"raw":"[Auer et al., 2007] Sören Auer, Christian Bizer, Georgi Ko- bilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. Dbpedia: A nucleus for a web of open data. The semantic web, pages 722-735, 2007.","title":"Dbpedia: A nucleus for a web of open data","authors":"Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, Zachary Ives","year":"2007","venue":"The semantic web","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bahdanau et al., 2014] Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. Neural machine translation by jointly learning to align and translate. In ICLR 2015, 2014.","title":"Neural machine translation by jointly learning to align and translate","authors":"Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio","year":"2014","venue":"ICLR 2015","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Bollacker et al., 2008] Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. Freebase: a collaboratively created graph database for structuring human knowledge. In Proceedings of the 2008 ACM SIGMOD international conference on Management of data, pages 1247-1250. AcM, 2008.","title":"Freebase: a collaboratively created graph database for structuring human knowledge","authors":"Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, Jamie Taylor","year":"2008","venue":"Proceedings of the 2008 ACM SIGMOD international conference on Management of data","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Carlson et al., 2010] Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R Hruschka Jr, and Tom M Mitchell. Toward an architecture for never-ending language learning. In AAAI, volume 5, page 3, 2010.","title":"Toward an architecture for never-ending language learning","authors":"Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, R Estevam, Tom M Hruschka, Mitchell","year":"2010","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Cho et al., 2014] Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. Learning phrase representations using rnn encoder-decoder for statistical machine translation. In Proceedings of the 2014 Confer- ence on Empirical Methods in Natural Language Process- ing (EMNLP), pages 1724-1734, Doha, Qatar, October 2014. Association for Computational Linguistics.","title":"Learning phrase representations using rnn encoder-decoder for statistical machine translation","authors":"Cho","year":"2014","venue":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Feng and Zhou, 2017] Ji Feng and Zhi-Hua Zhou. Deep miml network. In AAAI, pages 1884-1890, 2017.","title":"Deep miml network","authors":"Ji Feng, Zhi-Hua Zhou","year":"2017","venue":"AAAI","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Feng et al., 2017] Xiaocheng Feng, Jiang Guo, Bing Qin, T- ing Liu, and Yongjie Liu. Effective deep memory networks for distant supervised relation extraction. In Proceedings of the Twenty-Sixth International Joint Conference on Ar- tificial Intelligence, IJCAI, pages 19-25, 2017.","title":"Effective deep memory networks for distant supervised relation extraction","authors":"Xiaocheng Feng, Jiang Guo, Bing Qin, Ting Liu, Yongjie Liu","year":"2017","venue":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2017/559"},{"position":8,"raw":"[Hoffmann et al., 2011] Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, and Daniel S Weld. Knowledge-based weak supervision for information ex- traction of overlapping relations. In Proceedings of the 49th Annual Meeting of the Association for Computation- al Linguistics: Human Language Technologies-Volume 1, pages 541-550. Association for Computational Linguistic- s, 2011.","title":"Knowledge-based weak supervision for information extraction of overlapping relations","authors":"Raphael Hoffmann, Congle Zhang, Xiao Ling, Luke Zettlemoyer, Daniel S Weld","year":"2011","venue":"Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Jiang et al., 2016] Xiaotian Jiang, Quan Wang, Peng Li, and Bin Wang. Relation extraction with multi-instance multi- label convolutional neural networks. In COLING, pages 1471-1480, 2016.","title":"Relation extraction with multi-instance multilabel convolutional neural networks","authors":"Xiaotian Jiang, Quan Wang, Peng Li, Bin Wang","year":"2016","venue":"COLING","doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Jinchao Zhang, 2017] Jie Zhou Jinchao Zhang, Qun Liu. Me-md: An effective framework for neural machine trans- lation with multiple encoders and decoders. In Proceed- ings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17, pages 3392-3398, 2017.","title":"Me-md: An effective framework for neural machine translation with multiple encoders and decoders","authors":"Jie Zhou, Jinchao Zhang, Qun Liu","year":"2017","venue":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17","doi":null,"url":null,"internal_url":"/proceedings/2017/474"},{"position":11,"raw":"[Lin et al., 2016] Yankai Lin, Shiqi Shen, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. Neural relation extrac- tion with selective attention over instances. In ACL (1), 2016.","title":"Neural relation extraction with selective attention over instances","authors":"Lin","year":"2016","venue":"ACL","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Mikolov et al., 2013] Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. Distributed repre- sentations of words and phrases and their compositionali- ty. In Advances in neural information processing systems, pages 3111-3119, 2013.","title":"Distributed representations of words and phrases and their compositionality","authors":"Mikolov","year":"2013","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Mintz et al., 2009] Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. Distant supervision for relation extrac- tion without labeled data. In Proceedings of the Joint Con- ference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Pro- cessing of the AFNLP: Volume 2-Volume 2, pages 1003- 1011. Association for Computational Linguistics, 2009.","title":"Distant supervision for relation extraction without labeled data","authors":"Mike Mintz, Steven Bills, Rion Snow, Dan Jurafsky","year":"2009","venue":"Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Riedel et al., 2010] Sebastian Riedel, Limin Yao, and An- drew McCallum. Modeling relations and their mention- s without labeled text. Machine learning and knowledge discovery in databases, pages 148-163, 2010.","title":"Modeling relations and their mentions without labeled text","authors":"Sebastian Riedel, Limin Yao, Andrew Mccallum","year":"2010","venue":"Machine learning and knowledge discovery in databases","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Surdeanu et al., 2012] Mihai Surdeanu, Julie Tibshirani, Ramesh Nallapati, and Christopher D Manning. Multi- instance multi-label learning for relation extraction. In Proceedings of the 2012 joint conference on empirical methods in natural language processing and computation- al natural language learning, pages 455-465. Association for Computational Linguistics, 2012.","title":"Multiinstance multi-label learning for relation extraction","authors":"Mihai Surdeanu, Julie Tibshirani, Ramesh Nallapati, Christopher D Manning","year":"2012","venue":"Proceedings of the 2012 joint conference on empirical methods in natural language processing and computational natural language learning","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Sutskever et al., 2014] Ilya Sutskever, Oriol Vinyals, and Quoc V Le. Sequence to sequence learning with neural networks. In Advances in neural information processing systems, pages 3104-3112, 2014.","title":"Quoc V Le. Sequence to sequence learning with neural networks","authors":"Sutskever","year":"2014","venue":"Advances in neural information processing systems","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Vinyals et al., 2015] Oriol Vinyals, Łukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, and Geoffrey Hinton. Grammar as a foreign language. In Advances in Neural Information Processing Systems, pages 2773-2781, 2015.","title":"Grammar as a foreign language","authors":"Oriol Vinyals, Łukasz Kaiser, Terry Koo, Slav Petrov, Ilya Sutskever, Geoffrey Hinton","year":"2015","venue":"Advances in Neural Information Processing Systems","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[Wang et al., 2016] Jiang Wang, Yi Yang, Junhua Mao, Zhi- heng Huang, Chang Huang, and Wei Xu. Cnn-rnn: A u- nified framework for multi-label image classification. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 2285-2294, 2016.","title":"Cnn-rnn: A unified framework for multi-label image classification","authors":"Jiang Wang, Yi Yang, Junhua Mao, Zhiheng Huang, Chang Huang, Wei Xu","year":"2016","venue":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Ye et al., 2017] Hai Ye, Wenhan Chao, Zhunchen Luo, and Zhoujun Li. Jointly extracting relations with class ties via effective deep ranking. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 1810-1820, Vancouver, Canada, July 2017. Association for Computational Lin- guistics.","title":"Jointly extracting relations with class ties via effective deep ranking","authors":"Hai Ye, Wenhan Chao, Zhunchen Luo, Zhoujun Li","year":"2017","venue":"Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Zeng et al., 2015] Daojian Zeng, Kang Liu, Yubo Chen, and Jun Zhao. Distant supervision for relation extraction via piecewise convolutional neural networks. In Emnlp, pages 1753-1762, 2015.","title":"Distant supervision for relation extraction via piecewise convolutional neural networks","authors":"Zeng","year":"2015","venue":"Emnlp","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}