@inproceedings{wen-etal-2021-resin,
title = "{RESIN}: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System",
author = "Wen, Haoyang and
Lin, Ying and
Lai, Tuan and
Pan, Xiaoman and
Li, Sha and
Lin, Xudong and
Zhou, Ben and
Li, Manling and
Wang, Haoyu and
Zhang, Hongming and
Yu, Xiaodong and
Dong, Alexander and
Wang, Zhenhailong and
Fung, Yi and
Mishra, Piyush and
Lyu, Qing and
Sur{\'\i}s, D{\'\i}dac and
Chen, Brian and
Brown, Susan Windisch and
Palmer, Martha and
Callison-Burch, Chris and
Vondrick, Carl and
Han, Jiawei and
Roth, Dan and
Chang, Shih-Fu and
Ji, Heng",
editor = "Sil, Avi and
Lin, Xi Victoria",
booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations",
month = jun,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.naacl-demos.16",
doi = "10.18653/v1/2021.naacl-demos.16",
pages = "133--143",
abstract = "We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video). The system advances state-of-the-art from two aspects: (1) extending from sentence-level event extraction to cross-document cross-lingual cross-media event extraction, coreference resolution and temporal event tracking; (2) using human curated event schema library to match and enhance the extraction output. We have made the dockerlized system publicly available for research purpose at GitHub, with a demo video.",
}
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<abstract>We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video). The system advances state-of-the-art from two aspects: (1) extending from sentence-level event extraction to cross-document cross-lingual cross-media event extraction, coreference resolution and temporal event tracking; (2) using human curated event schema library to match and enhance the extraction output. We have made the dockerlized system publicly available for research purpose at GitHub, with a demo video.</abstract>
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%0 Conference Proceedings
%T RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System
%A Wen, Haoyang
%A Lin, Ying
%A Lai, Tuan
%A Pan, Xiaoman
%A Li, Sha
%A Lin, Xudong
%A Zhou, Ben
%A Li, Manling
%A Wang, Haoyu
%A Zhang, Hongming
%A Yu, Xiaodong
%A Dong, Alexander
%A Wang, Zhenhailong
%A Fung, Yi
%A Mishra, Piyush
%A Lyu, Qing
%A Surís, Dídac
%A Chen, Brian
%A Brown, Susan Windisch
%A Palmer, Martha
%A Callison-Burch, Chris
%A Vondrick, Carl
%A Han, Jiawei
%A Roth, Dan
%A Chang, Shih-Fu
%A Ji, Heng
%Y Sil, Avi
%Y Lin, Xi Victoria
%S Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
%D 2021
%8 June
%I Association for Computational Linguistics
%C Online
%F wen-etal-2021-resin
%X We present a new information extraction system that can automatically construct temporal event graphs from a collection of news documents from multiple sources, multiple languages (English and Spanish for our experiment), and multiple data modalities (speech, text, image and video). The system advances state-of-the-art from two aspects: (1) extending from sentence-level event extraction to cross-document cross-lingual cross-media event extraction, coreference resolution and temporal event tracking; (2) using human curated event schema library to match and enhance the extraction output. We have made the dockerlized system publicly available for research purpose at GitHub, with a demo video.
%R 10.18653/v1/2021.naacl-demos.16
%U https://aclanthology.org/2021.naacl-demos.16
%U https://doi.org/10.18653/v1/2021.naacl-demos.16
%P 133-143
Markdown (Informal)
[RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System](https://aclanthology.org/2021.naacl-demos.16) (Wen et al., NAACL 2021)
ACL
- Haoyang Wen, Ying Lin, Tuan Lai, Xiaoman Pan, Sha Li, Xudong Lin, Ben Zhou, Manling Li, Haoyu Wang, Hongming Zhang, Xiaodong Yu, Alexander Dong, Zhenhailong Wang, Yi Fung, Piyush Mishra, Qing Lyu, Dídac Surís, Brian Chen, Susan Windisch Brown, et al.. 2021. RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations, pages 133–143, Online. Association for Computational Linguistics.