no code implementations • 25 May 2022 • Nils Holzenberger, Yunmo Chen, Benjamin Van Durme
Information Extraction (IE) researchers are mapping tasks to Question Answering (QA) in order to leverage existing large QA resources, and thereby improve data efficiency.
2 code implementations • EMNLP 2021 • Mahsa Yarmohammadi, Shijie Wu, Marc Marone, Haoran Xu, Seth Ebner, Guanghui Qin, Yunmo Chen, Jialiang Guo, Craig Harman, Kenton Murray, Aaron Steven White, Mark Dredze, Benjamin Van Durme
Zero-shot cross-lingual information extraction (IE) describes the construction of an IE model for some target language, given existing annotations exclusively in some other language, typically English.
no code implementations • EACL 2021 • Patrick Xia, Guanghui Qin, Siddharth Vashishtha, Yunmo Chen, Tongfei Chen, Chandler May, Craig Harman, Kyle Rawlins, Aaron Steven White, Benjamin Van Durme
We present LOME, a system for performing multilingual information extraction.
no code implementations • 21 Dec 2020 • Yunmo Chen, Sixing Lu, Fan Yang, Xiaojiang Huang, Xing Fan, Chenlei Guo
Query rewriting (QR) systems are widely used to reduce the friction caused by errors in a spoken language understanding pipeline.
1 code implementation • 20 Nov 2020 • Yunmo Chen, Tongfei Chen, Benjamin Van Durme
We recognize the task of event argument linking in documents as similar to that of intent slot resolution in dialogue, providing a Transformer-based model that extends from a recently proposed solution to resolve references to slots.
1 code implementation • ACL 2020 • Tongfei Chen, Yunmo Chen, Benjamin Van Durme
We propose a novel method for hierarchical entity classification that embraces ontological structure at both training and during prediction.
no code implementations • EMNLP (spnlp) 2020 • Yunmo Chen, Tongfei Chen, Seth Ebner, Aaron Steven White, Benjamin Van Durme
We ask whether text understanding has progressed to where we may extract event information through incremental refinement of bleached statements derived from annotation manuals.