2021
NAACL
NAACL 2021
RESIN: A Dockerized Schema-Guided Cross-document Cross-lingual Cross-media Information Extraction and Event Tracking System
Abstract
AbstractWe 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.
👥
Mega-Team
— 26 authors
🧭
Keyword Pioneer
— cross-document information extraction
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy
Authors
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
,
Didac Suris
,
Brian Chen
,
Susan Windisch Brown
,
Martha Palmer
,
Chris Callison-Burch
,
Carl Vondrick
,
Jiawei Han
,
Dan Roth
,
Shih-fu Chang
,
Heng Ji