TY - GEN
T1 - Event-centric natural language processing
AU - Chen, Muhao
AU - Zhang, Hongming
AU - Ning, Qiang
AU - Li, Manling
AU - Ji, Heng
AU - McKeown, Kathleen
AU - Roth, Dan
N1 - Publisher Copyright:
© 2021 Association for Computational Linguistics.
PY - 2021
Y1 - 2021
N2 - This tutorial targets researchers and practitioners who are interested in AI technologies that help machines understand natural language text, particularly real-world events described in the text. These include methods to extract the internal structures of an event regarding its protagonist(s), participant(s) and properties, as well as external structures concerning memberships, temporal and causal relations of multiple events. This tutorial will provide audience with a systematic introduction of (i) knowledge representations and acquisition of events, (ii) various methods for automated extraction, conceptualization, coreference resolution and prediction of events and their relations, (iii) induction of event processes and properties, and (iv) a wide range of NLP and commonsense understanding tasks that benefit from aforementioned techniques. We will conclude the tutorial by outlining emerging research problems in this area.
AB - This tutorial targets researchers and practitioners who are interested in AI technologies that help machines understand natural language text, particularly real-world events described in the text. These include methods to extract the internal structures of an event regarding its protagonist(s), participant(s) and properties, as well as external structures concerning memberships, temporal and causal relations of multiple events. This tutorial will provide audience with a systematic introduction of (i) knowledge representations and acquisition of events, (ii) various methods for automated extraction, conceptualization, coreference resolution and prediction of events and their relations, (iii) induction of event processes and properties, and (iv) a wide range of NLP and commonsense understanding tasks that benefit from aforementioned techniques. We will conclude the tutorial by outlining emerging research problems in this area.
UR - http://www.scopus.com/inward/record.url?scp=85106408007&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:85106408007
T3 - ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Tutorial Abstracts
SP - 6
EP - 14
BT - ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Tutorial Abstracts
PB - Association for Computational Linguistics (ACL)
T2 - Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, ACL-IJCNLP 2021
Y2 - 1 August 2021
ER -