About: Automatic Textual Evidence Mining in COVID-19 Literature

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Automatic Textual Evidence Mining in COVID-19 Literature
Creator	Wang, Xuan Guan, Yingjun Han, Jiawei Chauhan, Aabhas Liu, Weili
source	ArXiv
abstract	We created this EVIDENCEMINER system for automatic textual evidence mining in COVID-19 literature. EVIDENCEMINER is a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background corpora for life sciences. It is constructed in a completely automated way without any human effort for training data annotation. EVIDENCEMINER is supported by novel data-driven methods for distantly supervised named entity recognition and open information extraction. The named entities and meta-patterns are pre-computed and indexed offline to support fast online evidence retrieval. The annotation results are also highlighted in the original document for better visualization. EVIDENCEMINER also includes analytic functionalities such as the most frequent entity and relation summarization.
has issue date	2020-04-27(xsd:dateTime)
has license	arxiv
sha1sum (hex)	e3e74a23b47b2ff4241580bd5346598bd68b41b8
resource representing a document's title	Automatic Textual Evidence Mining in COVID-19 Literature
resource representing a document's body	covid:e3e74a23b47b2ff4241580bd5346598bd68b41b8#body_text
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