Fetching the paper…
Reading the bibliography…
We present the first human-annotated dialogue-based relation extraction (RE) dataset DialogRE, aiming to support the prediction of relation(s) between two arguments that appear in a dialogue.
Simple BERT models for relation extraction and semantic role labeling
Peng Shi and Jimmy Lin. 2019 · 1904
Earlier work this paper cites.
Variation across speech and writing
Douglas Biber. 1991 · 1991
Earlier work this paper cites.
The automatic content extraction (ACE) program – tasks, data, and evaluation
George Doddington, Alexis Mitchell, Mark Przybocki, Lance Ramshaw, Stephanie Strassel, and Ralph Weischedel. 2004 · 2004
Earlier work this paper cites.
A linear programming formulation for global inference in natural language tasks
Dan Roth and Wen-tau Yih. 2004 · 2004
Earlier work this paper cites.
Overview of the TAC 2009 knowledge base population track
Paul McNamee and Hoa Trang Dang. 2009 · 2009
Earlier work this paper cites.
Distant supervision for relation extraction without labeled data
Mike Mintz, Steven Bills, Rion Snow, and Dan Jurafsky. 2009 · 2009
Earlier work this paper cites.
Television dialogue: The sitcom Friends vs. natural conversation , volume 36
Paulo Quaglio. 2009 · 2009
Earlier work this paper cites.
Using dialogue corpora to extend information extraction patterns for natural language understanding of dialogue
Roberta Catizone, Alexiei Dingli, and Robert Gaizauskas. 2010 · 2010
Earlier work this paper cites.
SemEval-2010 task 8: Multi-way classification of semantic relations between pairs of nominals
Iris Hendrickx, Su Nam Kim, Zornitsa Kozareva, Preslav Nakov, Diarmuid Ó Séaghdha, Sebastian Padó, Marco Pennacchiotti, Lorenza Romano, and Stan Szpakowicz. 2010 · 2010
Earlier work this paper cites.
Overview of the TAC 2010 knowledge base population track
Heng Ji, Ralph Grishman, Hoa Trang Dang, Kira Griffitt, and Joe Ellis. 2010 · 2010
Earlier work this paper cites.
Using syntactic and semantic based relations for dialogue act recognition
Tina Klüwer, Hans Uszkoreit, and Feiyu Xu. 2010 · 2010
Earlier work this paper cites.
SemEval-2010 task 13: Evaluating events, time expressions, and temporal relations (TempEval-2)
James Pustejovsky and Marc Verhagen. 2009 · 2010
Earlier work this paper cites.
Modeling relations and their mentions without labeled text
Sebastian Riedel, Limin Yao, and Andrew McCallum. 2010 · 2010
Earlier work this paper cites.
Inter-sentential relations in information extraction corpora
Kumutha Swampillai and Mark Stevenson. 2010 · 2010
Earlier work this paper cites.
Overview of the TAC2011 Knowledge Base Population Track
Heng Ji, Ralph Grishman, and Hoa Trang Dang. 2011 · 2011
Earlier work this paper cites.
English gigaword fifth edition, linguistic data consortium
Robert Parker, David Graff, Junbo Kong, Ke Chen, and Kazuaki Maeda. 2011 · 2011
Earlier work this paper cites.
A pilot study of opinion summarization in conversations
Dong Wang and Yang Liu. 2011 · 2011
Earlier work this paper cites.
Spoken dialogue system based on information extraction using similarity of predicate argument structures
Koichiro Yoshino, Shinsuke Mori, and Tatsuya Kawahara. 2011 · 2011
Earlier work this paper cites.
Joint inference for event timeline construction
Quang Do, Wei Lu, and Dan Roth. 2012 · 2012
Earlier work this paper cites.
Focused meeting summarization via unsupervised relation extraction
Lu Wang and Claire Cardie. 2012 · 2012
Earlier work this paper cites.
Long-distance time-event relation extraction
Alessandro Moschitti, Siddharth Patwardhan, and Chris Welty. 2013 · 2013
Earlier work this paper cites.
Overview of the TAC2013 knowledge base population evaluation: English slot filling and temporal slot filling
Mihai Surdeanu. 2013 · 2013
Earlier work this paper cites.
A comparison of the events and relations across ACE, ERE, TAC-KBP, and FrameNet annotation standards
Jacqueline Aguilar, Charley Beller, Paul McNamee, Benjamin Van Durme, Stephanie Strassel, Zhiyi Song, and Joe Ellis. 2014 · 2014
Earlier work this paper cites.
Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
Earlier work this paper cites.
Overview of the english slot filling track at the TAC2014 knowledge base population evaluation
Mihai Surdeanu and Heng Ji. 2014 · 2014
Cited alongside, same era.
Relation classification via convolutional deep neural network
Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. 2014 · 2014
Cited alongside, same era.
Seed-based event trigger labeling: How far can event descriptions get us?
Ofer Bronstein, Ido Dagan, Qi Li, Heng Ji, and Anette Frank. 2015 · 2015
Cited alongside, same era.
Learning knowledge graphs for question answering through conversational dialog
Ben Hixon, Peter Clark, and Hannaneh Hajishirzi. 2015 · 2015
Cited alongside, same era.
Argument mining: Extracting arguments from online dialogue
Reid Swanson, Brian Ecker, and Marilyn Walker. 2015 · 2015
Cited alongside, same era.
Classifying relations via long short term memory networks along shortest dependency paths
T-REx: A large scale alignment of natural language with knowledge base triples
Hady Elsahar, Pavlos Vougiouklis, Arslen Remaci, Christophe Gravier, Jonathon Hare, Frédérique Laforest, and Elena Simperl. 2018 · 2018
Later among the works it cites.
FewRel: A large-scale supervised few-shot relation classification dataset with state-of-the-art evaluation
Xu Han, Hao Zhu, Pengfei Yu, Ziyun Wang, Yuan Yao, Zhiyuan Liu, and Maosong Sun. 2018 · 2018
Later among the works it cites.
Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 2018 · 2018
Later among the works it cites.
Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Later among the works it cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yan Xu, Lili Mou, Ge Li, Yunchuan Chen, Hao Peng, and Zhi Jin. 2015 · 2015
Cited alongside, same era.
Distant supervision for relation extraction via piecewise convolutional neural networks
Daojian Zeng, Kang Liu, Yubo Chen, and Jun Zhao. 2015 · 2015
Cited alongside, same era.
Relation classification via recurrent neural network
Dongxu Zhang and Dong Wang. 2015 · 2015
Cited alongside, same era.
Comparing convolutional neural networks to traditional models for slot filling
Heike Adel, Benjamin Roth, and Hinrich Schütze. 2016 · 2016
Cited alongside, same era.
Bidirectional recurrent convolutional neural network for relation classification
Rui Cai, Xiaodong Zhang, and Houfeng Wang. 2016 · 2016
Cited alongside, same era.
Character identification on multiparty conversation: Identifying mentions of characters in TV shows
Yu-Hsin Chen and Jinho D. Choi. 2016 · 2016
Cited alongside, same era.
BioCreative V CDR task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016 · 2016
Cited alongside, same era.
Characterizing interactions and relationships between people
Farzana Rashid and Eduardo Blanco. 2018 · 2018
Later among the works it cites.
N-ary relation extraction using graph-state lstm
Linfeng Song, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2018 · 2018
Later among the works it cites.
Global relation embedding for relation extraction
Yu Su, Honglei Liu, Semih Yavuz, Izzeddin Gür, Huan Sun, and Xifeng Yan. 2018 · 2018
Later among the works it cites.
Emotion detection on tv show transcripts with sequence-based convolutional neural networks
Sayyed M Zahiri and Jinho D Choi. 2018 · 2018
Later among the works it cites.
They exist! introducing plural mentions to coreference resolution and entity linking
Ethan Zhou and Jinho D Choi. 2018 · 2018
Later among the works it cites.
Improving relation extraction by pre-trained language representations
Christoph Alt, Marc Hübner, and Leonhard Hennig. 2019 · 2019
Later among the works it cites.
Matching the blanks: Distributional similarity for relation learning
Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, and Tom Kwiatkowski. 2019 · 2019
Later among the works it cites.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
Twenty-five years of information extraction
Ralph Grishman. 2019 · 2019
Later among the works it cites.
Semi-supervised teacher-student architecture for relation extraction
Fan Luo, Ajay Nagesh, Rebecca Sharp, and Mihai Surdeanu. 2019 · 2019
Later among the works it cites.
KnowledgeNet: A benchmark dataset for knowledge base population
Filipe Mesquita, Matteo Cannaviccio, Jordan Schmidek, Paramita Mirza, and Denilson Barbosa. 2019 · 2019
Later among the works it cites.
Knowledge enhanced contextual word representations
Matthew E. Peters, Mark Neumann, Robert Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith. 2019 · 2019
Later among the works it cites.
DREAM: A challenge dataset and models for dialogue-based reading comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, and Claire Cardie. 2019 · 2019
Later among the works it cites.
Entity, relation, and event extraction with contextualized span representations
David Wadden, Ulme Wennberg, Yi Luan, and Hannaneh Hajishirzi. 2019 · 2019
Later among the works it cites.
FriendsQA: Open-domain question answering on tv show transcripts
Zhengzhe Yang and Jinho D Choi. 2019 · 2019
Later among the works it cites.
DocRED: A large-scale document-level relation extraction dataset
Yuan Yao, Deming Ye, Peng Li, Xu Han, Yankai Lin, Zhenghao Liu, Zhiyuan Liu, Lixin Huang, Jie Zhou, and Maosong Sun. 2019 · 2019
Later among the works it cites.
Spanbert: Improving pre-training by representing and predicting spans
Mandar Joshi, Danqi Chen, Yinhan Liu, Daniel S Weld, Luke Zettlemoyer, and Omer Levy. 2020 · 2020
Closest in time.
Challenging reading comprehension on daily conversation: Passage completion on multiparty dialog
Kaixin Ma, Tomasz Jurczyk, and Jinho D. Choi. 2018 · 2048
Closest in time.