Dídac Surís
2021
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System
Haoyang Wen
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Ying Lin
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Tuan Lai
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Xiaoman Pan
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Sha Li
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Xudong Lin
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Ben Zhou
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Manling Li
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Haoyu Wang
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Hongming Zhang
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Xiaodong Yu
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Alexander Dong
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Zhenhailong Wang
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Yi Fung
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Piyush Mishra
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Qing Lyu
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Dídac Surís
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Brian Chen
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Susan Windisch Brown
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Martha Palmer
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Chris Callison-Burch
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Carl Vondrick
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Jiawei Han
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Dan Roth
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Shih-Fu Chang
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Heng Ji
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations
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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Co-authors
- Alexander Dong 1
- Ben Zhou 1
- Brian Chen 1
- Carl Vondrick 1
- Chris Callison-Burch 1
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