{"type":"ScholarlyArticle","title":"A Survey on Temporal Reasoning for Temporal Information Extraction from Text (Extended Abstract)","authors":[{"name":"Artuur Leeuwenberg","slug":"artuur-leeuwenberg","given":"Artuur","family":"Leeuwenberg","affiliation":"Julius Center , University Medical Center Utrecht , The Netherlands"},{"name":"Marie-Francine Moens","slug":"marie-francine-moens","given":"Marie-Francine","family":"Moens","affiliation":"Department of Computer Science , KU Leuven , Belgium"}],"abstract":"Time is deeply woven into how people perceive, and communicate about the world. Almost unconsciously, we provide our language utterances with temporal cues, like verb tenses, and we can hardly produce sentences without such cues. \r\nExtracting temporal cues from text, and constructing a global temporal view about the order of described events is a major challenge of automatic natural language understanding. Temporal reasoning, the process of combining different temporal cues into a coherent temporal view, plays a central role in temporal information extraction. This article presents a comprehensive survey of the research from the past decades on temporal reasoning for automatic temporal information extraction from text, providing a case study on the integration of symbolic reasoning with machine learning-based information extraction systems.","doi":"10.24963/ijcai.2020/712","url":"https://ijcai.org/proceedings/2020/712","pdf":"https://ijcai.org/proceedings/2020/0712.pdf","markdown":"https://ijcai.org/proceedings/2020/712.md","bibtex":"https://ijcai.org/proceedings/2020/bibtex/712","volume":{"slug":"2020","title":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2020","url":"https://ijcai.org/proceedings/2020/","year":2020,"location":"Yokohama","dates":"January 2021 (postponed from 11-17 July 2020)","editors":"Christian Bessiere","isbn":"978-0-9992411-6-5","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2020"},"section":"Journal track","track":"Journal track","number":712,"pages":{"first":5085,"last":5089},"keywords":["Machine Learning: Structured Prediction","Natural Language Processing: Information Extraction","Natural Language Processing: Natural Language Semantics","Knowledge Representation and Reasoning: Qualitative, Geometric, Spatial, Temporal Reasoning"],"videos":[{"label":"Video","url":"https://videos.ijcai20.org/25565/file_25565.m3u8","length_sec":284,"provider":"hls"}],"references":[{"position":1,"raw":"[Allen, 1983] James F Allen. Maintaining knowledge about temporal intervals. In Communications of the ACM, pp. 832-843. ACM, 1983.","title":"Maintaining knowledge about temporal intervals","authors":"James F Allen","year":"1983","venue":"Communications of the ACM","doi":null,"url":null,"internal_url":null},{"position":2,"raw":"[Bramsen et al., 2006] Philip Bramsen, Pawan Deshpande, Yoong Keok Lee, and Regina Barzilay. Inducing temporal graphs. In Proc. EMNLP, pp. 189-198. ACL, 2006.","title":"Inducing temporal graphs","authors":"Philip Bramsen, Pawan Deshpande, Yoong Keok Lee, Regina Barzilay","year":"2006","venue":"Proc. EMNLP","doi":null,"url":null,"internal_url":null},{"position":3,"raw":"[Campos et al., 2015] Ricardo Campos, Gaël Dias, Alípio M Jorge, and Adam Jatowt. Survey of temporal information retrieval and related applications. ACM Computing Sur- veys, 47(2):15, 2015.","title":"Survey of temporal information retrieval and related applications","authors":"Ricardo Campos, Gaël Dias, Alípio M Jorge, Adam Jatowt","year":"2015","venue":"ACM Computing Surveys","doi":null,"url":null,"internal_url":null},{"position":4,"raw":"[Cassidy et al., 2014] Taylor Cassidy, Bill McDowell, Nathanael Chambers, and Steven Bethard. An annotation framework for dense event ordering. In Proc. ACL, vol. 2, pp. 501-506. ACL, 2014.","title":"An annotation framework for dense event ordering","authors":"Taylor Cassidy, Bill Mcdowell, Nathanael Chambers, Steven Bethard","year":"2014","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":5,"raw":"[Chambers and Jurafsky, 2008] Nathanael Chambers and Dan Jurafsky. Jointly combining implicit constraints improves temporal ordering. In Proc. EMNLP, pp. 698-706. ACL, 2008.","title":"Jointly combining implicit constraints improves temporal ordering","authors":"Jurafsky Chambers, Nathanael Chambers, Dan Jurafsky","year":"2008","venue":"Proc. EMNLP","doi":null,"url":null,"internal_url":null},{"position":6,"raw":"[Chambers et al., 2014] Nathanael Chambers, Taylor Cas- sidy, Bill McDowell, and Steven Bethard. Dense event ordering with a multi-pass architecture. In Transactions of the ACL, vol. 2, pp. 273-284, 2014.","title":"Dense event ordering with a multi-pass architecture","authors":"Chambers","year":"2014","venue":"Transactions of the ACL","doi":null,"url":null,"internal_url":null},{"position":7,"raw":"[Denis and Muller, 2011] Pascal Denis and Philippe Muller. Predicting globally-coherent temporal structures from texts via endpoint inference and graph decomposition. In Proc. IJCAI, pp. 1788-1793, 2011.","title":"Predicting globally-coherent temporal structures from texts via endpoint inference and graph decomposition","authors":"Denis, Muller, Pascal Denis, Philippe Muller","year":"2011","venue":"Proc. IJCAI","doi":null,"url":null,"internal_url":"/proceedings/2011/300"},{"position":8,"raw":"[Derczynski, 2016] Leon Derczynski. Representation and learning of temporal relations. In Proc. COLING, pp. 1937-1948. ACL, 2016.","title":"Representation and learning of temporal relations","authors":"Leon Derczynski","year":"2016","venue":"Proc. COLING","doi":null,"url":null,"internal_url":null},{"position":9,"raw":"[Derczynski, 2017] Leon RA Derczynski. Automatically Or- dering Events and Times in Text. Springer, 2017.","title":"Automatically Ordering Events and Times in Text","authors":"R A Leon, Derczynski","year":"2017","venue":null,"doi":null,"url":null,"internal_url":null},{"position":10,"raw":"[Freksa, 1992] Christian Freksa. Temporal reasoning based on semi-intervals. In Artificial Intelligence, vol. 54, pp. 199-227. Elsevier, 1992.","title":"Christian Freksa. Temporal reasoning based on semi-intervals","authors":"Freksa","year":"1992","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":11,"raw":"[Jung et al., 2011] Hyuckchul Jung, James Allen, Nate Blay- lock, Will De Beaumont, Lucian Galescu, and Mary Swift. Building timelines from narrative clinical records: initial results based-on deep natural language understanding. In Proc. BioNLP, pp. 146-154, 2011.","title":"Building timelines from narrative clinical records: initial results based-on deep natural language understanding","authors":"Jung","year":"2011","venue":"Proc. BioNLP","doi":null,"url":null,"internal_url":null},{"position":12,"raw":"[Krokhin et al., 2003] Andrei Krokhin, Peter Jeavons, and Peter Jonsson. Reasoning about temporal relations: The tractable subalgebras of Allen's interval algebra. In Jour- nal of the ACM, vol. 50, pp. 591-640. ACM, 2003.","title":"Reasoning about temporal relations: The tractable subalgebras of Allen's interval algebra","authors":"Krokhin","year":"2003","venue":"Journal of the ACM","doi":null,"url":null,"internal_url":null},{"position":13,"raw":"[Laokulrat et al., 2015] Natsuda Laokulrat, Makoto Miwa, and Yoshimasa Tsuruoka. Stacking approach to temporal relation classification with temporal inference. In Journal of NLP, vol. 22, pp. 171-196, 2015.","title":"Stacking approach to temporal relation classification with temporal inference","authors":"Laokulrat","year":"2015","venue":"Journal of NLP","doi":null,"url":null,"internal_url":null},{"position":14,"raw":"[Leeuwenberg and Moens, 2017] Artuur Leeuwenberg and Marie-Francine Moens. Structured learning for temporal relation extraction from clinical records. In Proc. EACL, pp. 1150-1158. ACL, 2017.","title":"Artuur Leeuwenberg and Marie-Francine Moens. Structured learning for temporal relation extraction from clinical records","authors":"Moens Leeuwenberg","year":"2017","venue":"Proc. EACL","doi":null,"url":null,"internal_url":null},{"position":15,"raw":"[Leeuwenberg and Moens, 2018] Artuur Leeuwenberg and Marie-Francine Moens. Temporal information extraction by predicting relative time-lines. In Proc. EMNLP, pp. 1237-1246, 2018.","title":"Artuur Leeuwenberg and Marie-Francine Moens. Temporal information extraction by predicting relative time-lines","authors":"Moens Leeuwenberg","year":"2018","venue":"Proc. EMNLP","doi":null,"url":null,"internal_url":null},{"position":16,"raw":"[Leeuwenberg and Moens, 2019] Artuur Leeuwenberg and Marie-Francine Moens. A survey on temporal reasoning for temporal information extraction from text. Journal of Artificial Intelligence Research, 66:341-380, 2019.","title":"Artuur Leeuwenberg and Marie-Francine Moens. A survey on temporal reasoning for temporal information extraction from text","authors":"Moens Leeuwenberg","year":"2019","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":17,"raw":"[Mani et al., 2006] Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong Min Lee, and James Pustejovsky. Machine learning of temporal relations. In Proc. COLING-ACL, pp. 753-760. ACL, 2006.","title":"Machine learning of temporal relations","authors":"Inderjeet Mani, Marc Verhagen, Ben Wellner, Chong, Min Lee, James Pustejovsky","year":"2006","venue":"Proc. COLING-ACL","doi":null,"url":null,"internal_url":null},{"position":18,"raw":"[McDowell et al., 2017] Bill McDowell, Nathanael Cham- bers, Alexander Ororbia II, and David Reitter. Event order- ing with a generalized model for sieve prediction ranking. In Proc. IJCNLP, vol. 1, pp. 843-853. ACL, 2017.","title":"Bill McDowell, Nathanael Chambers, Alexander Ororbia II, and David Reitter. Event ordering with a generalized model for sieve prediction ranking","authors":"Mcdowell","year":"2017","venue":"Proc. IJCNLP","doi":null,"url":null,"internal_url":null},{"position":19,"raw":"[Meiri, 1996] Itay Meiri. Combining qualitative and quanti- tative constraints in temporal reasoning. In Artificial Intel- ligence, vol. 87, pp. 343-385, 1996.","title":"Combining qualitative and quantitative constraints in temporal reasoning","authors":"Itay Meiri","year":"1996","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":20,"raw":"[Meng and Rumshisky, 2018] Yuanliang Meng and Anna Rumshisky. Context-aware neural model for temporal in- formation extraction. In Proc. ACL, vol. 1, pp. 527-536. ACL, 2018.","title":"Yuanliang Meng and Anna Rumshisky. Context-aware neural model for temporal information extraction","authors":"Rumshisky Meng","year":"2018","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":21,"raw":"[Meng et al., 2017] Yuanliang Meng, Anna Rumshisky, and Alexey Romanov. Temporal information extraction for question answering using syntactic dependencies in an LSTM-based architecture. In Proc. EMNLP, pp. 887-896. ACL, 2017.","title":"Temporal information extraction for question answering using syntactic dependencies in an LSTM-based architecture","authors":"Meng","year":"2017","venue":"Proc. EMNLP","doi":null,"url":null,"internal_url":null},{"position":22,"raw":"[Mirza and Tonelli, 2016] Paramita Mirza and Sara Tonelli. Catena: Causal and temporal relation extraction from nat- ural language texts. In Proc. COLING, pp. 64-75. ACL, 2016.","title":"Catena: Causal and temporal relation extraction from natural language texts","authors":"Tonelli Mirza, Paramita Mirza, Sara Tonelli","year":"2016","venue":"Proc. COLING","doi":null,"url":null,"internal_url":null},{"position":23,"raw":"[Mojica and Ng, 2016] Luis Gerardo Mojica and Vincent Ng. Markov Logic Networks for text mining: A quali- tative and empirical comparison with ILP. In Proc. LREC, pp. 4388-4395, 2016.","title":"Markov Logic Networks for text mining: A qualitative and empirical comparison with ILP","authors":"Ng ; Mojica, Gerardo Luis, Vincent Mojica, Ng","year":"2016","venue":"Proc. LREC","doi":null,"url":null,"internal_url":null},{"position":24,"raw":"[Ng et al., 2014] Jun-Ping Ng, Yan Chen, Min-Yen Kan, and Zhoujun Li. Exploiting timelines to enhance multi- document summarization. In Proc. ACL, vol. 1, pp. 923- 933. ACL, 2014.","title":"Exploiting timelines to enhance multidocument summarization","authors":"Ng","year":"2014","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":25,"raw":"[Ning et al., 2017] Qiang Ning, Zhili Feng, and Dan Roth. A structured learning approach to temporal relation extrac- tion. In Proc. EMNLP, pp. 1027-1037. ACL, 2017.","title":"A structured learning approach to temporal relation extraction","authors":"Qiang Ning, Zhili Feng, Dan Roth","year":"2017","venue":"Proc. EMNLP","doi":null,"url":null,"internal_url":null},{"position":26,"raw":"[Ning et al., 2018] Qiang Ning, Hao Wu, and Dan Roth. A multi-axis annotation scheme for event temporal relations. In Proc. ACL, pp. 1318-1328, 2018.","title":"A multi-axis annotation scheme for event temporal relations","authors":"Qiang Ning, Hao Wu, Dan Roth","year":"2018","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":27,"raw":"[Pan et al., 2006] Feng Pan, Rutu Mulkar-Mehta, and Jerry R Hobbs. An annotated corpus of typical durations of events. In Proc. LREC, pp. 77-82, 2006.","title":"An annotated corpus of typical durations of events","authors":"Pan","year":"2006","venue":"Proc. LREC","doi":null,"url":null,"internal_url":null},{"position":28,"raw":"[Pustejovsky et al., 2003] James Pustejovsky, José M Cas- tano, Robert Ingria, Roser Sauri, Robert J Gaizauskas, Andrea Setzer, Graham Katz, and Dragomir R Radev. TimeML: Robust specification of event and temporal ex- pressions in text. In New Directions in QA, vol. 3, pp. 28-34, 2003.","title":"TimeML: Robust specification of event and temporal expressions in text","authors":"James Pustejovsky, M José, Robert Castano, Roser Ingria, Robert J Sauri, Andrea Gaizauskas, Graham Setzer, Katz, Dragomir R Radev","year":"2003","venue":"New Directions in QA","doi":null,"url":null,"internal_url":null},{"position":29,"raw":"[Raghavan et al., 2014] Preethi Raghavan, James L Chen, Eric Fosler-Lussier, and Albert M Lai. How essential are unstructured clinical narratives and information fusion to clinical trial recruitment? In AMIA Jt. Summits Transl. Sci. Proc., pp. 218-223, 2014.","title":"How essential are unstructured clinical narratives and information fusion to clinical trial recruitment?","authors":"Preethi Raghavan, Eric James L Chen, Albert M Fosler-Lussier, Lai","year":"2014","venue":"AMIA Jt. Summits Transl. Sci. Proc","doi":null,"url":null,"internal_url":null},{"position":30,"raw":"[Reimers et al., 2016] Nils Reimers, Nazanin Dehghani, and Iryna Gurevych. Temporal anchoring of events for the TimeBank corpus. In Proc. ACL, vol. 1, pp. 2195-2204, 2016.","title":"Temporal anchoring of events for the TimeBank corpus","authors":"Reimers","year":"2016","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":31,"raw":"[Schockaert and De Cock, 2008] Steven Schockaert and Martine De Cock. Temporal reasoning about fuzzy inter- vals. In Artificial Intelligence, vol. 172, pp. 1158-1193. Elsevier, 2008.","title":"Temporal reasoning about fuzzy intervals","authors":"De Schockaert, Steven Cock, Martine De Schockaert, Cock","year":"2008","venue":"Artificial Intelligence","doi":null,"url":null,"internal_url":null},{"position":32,"raw":"[Setzer et al., 2003] Andrea Setzer, Robert Gaizauskas, and Mark Hepple. Using semantic inferences for temporal an- notation comparison. In Proc. IWCS, 2003.","title":"Using semantic inferences for temporal annotation comparison","authors":"Andrea Setzer, Robert Gaizauskas, Mark Hepple","year":"2003","venue":"Proc. IWCS","doi":null,"url":null,"internal_url":null},{"position":33,"raw":"[Tannier and Muller, 2011] Xavier Tannier and Philippe Muller. Evaluating temporal graphs built from texts via transitive reduction. In Journal of Artificial Intelligence Research, vol. 40, pp. 375-413, 2011.","title":"Xavier Tannier and Philippe Muller. Evaluating temporal graphs built from texts via transitive reduction","authors":"Muller Tannier","year":"2011","venue":"Journal of Artificial Intelligence Research","doi":null,"url":null,"internal_url":null},{"position":34,"raw":"[Tatu and Srikanth, 2008] Marta Tatu and Munirathnam Srikanth. Experiments with reasoning for temporal rela- tions between events. In Proc. COLING, pp. 857-864. ACL, 2008.","title":"Experiments with reasoning for temporal relations between events","authors":"Srikanth Tatu, Marta Tatu, Munirathnam Srikanth","year":"2008","venue":"Proc. COLING","doi":null,"url":null,"internal_url":null},{"position":35,"raw":"[UzZaman and Allen, 2011] Naushad UzZaman and James F. Allen. Temporal evaluation. In Proc. ACL, pp. 351-356, 2011.","title":"Temporal evaluation","authors":"Naushad Uzzaman, James F Allen","year":"2011","venue":"Proc. ACL","doi":null,"url":null,"internal_url":null},{"position":36,"raw":"[Verhagen and Pustejovsky, 2008] Marc Verhagen and James Pustejovsky. Temporal processing with the TARSQI toolkit. In Proc. COLING, pp. 189-192. ACL, 2008.","title":"Temporal processing with the TARSQI toolkit","authors":"Pustejovsky Verhagen, Marc Verhagen, James Pustejovsky","year":"2008","venue":"Proc. COLING","doi":null,"url":null,"internal_url":null},{"position":37,"raw":"[Verhagen et al., 2007] Marc Verhagen, Robert Gaizauskas, Frank Schilder, Mark Hepple, Graham Katz, and James Pustejovsky. SemEval-2007 Task 15: TempEval temporal relation identification. In Proc. SemEval, pp. 75-80. ACL, 2007.","title":"SemEval-2007 Task 15: TempEval temporal relation identification","authors":"Marc Verhagen, Robert Gaizauskas, Frank Schilder, Mark Hepple, Graham Katz, James Pustejovsky","year":"2007","venue":"Proc. SemEval","doi":null,"url":null,"internal_url":null},{"position":38,"raw":"[Verhagen, 2005] Marc Verhagen. Temporal closure in an annotation environment. In Language Resources and Eval- uation, vol. 39, pp. 211-241, 2005.","title":"Temporal closure in an annotation environment","authors":"Marc Verhagen","year":"2005","venue":"Language Resources and Evaluation","doi":null,"url":null,"internal_url":null},{"position":39,"raw":"[Vilain et al., 1990] Marc Vilain, Henry Kautz, and Peter Van Beek. Constraint propagation algorithms for temporal reasoning: A revised report. In Readings in Qualitative Reasoning about Physical Systems, pp. 373-381. Elsevier, 1990.","title":"Constraint propagation algorithms for temporal reasoning: A revised report","authors":"Marc Vilain, Henry Kautz, Peter Van Beek","year":"1990","venue":"Readings in Qualitative Reasoning about Physical Systems","doi":null,"url":null,"internal_url":null},{"position":40,"raw":"[Yoshikawa et al., 2009] Katsumasa Yoshikawa, Sebastian Riedel, Masayuki Asahara, and Yuji Matsumoto. Jointly identifying temporal relations with Markov logic. In Proc. ACL-IJCNLP, pp. 405-413, 2009.","title":"Jointly identifying temporal relations with Markov logic","authors":"Yoshikawa","year":"2009","venue":"Proc. ACL-IJCNLP","doi":null,"url":null,"internal_url":null},{"position":41,"raw":"[Zhou and Hripcsak, 2007] Li Zhou and George Hripcsak. Temporal reasoning with medical data -a review with emphasis on medical natural language processing. In J. Biomed. Inform., vol. 40, pp. 183-202, 2007.","title":"Temporal reasoning with medical data -a review with emphasis on medical natural language processing","authors":"Li Zhou, George Hripcsak","year":"2007","venue":"J. Biomed. Inform","doi":null,"url":null,"internal_url":null}],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}