Open AccessProceedings Article
Overview of BioNLP Shared Task 2013
Claire Nédellec,Robert Bossy,Jin-Dong Kim,Jung-Jae Kim,Tomoko Ohta,Sampo Pyysalo,Pierre Zweigenbaum +6 more
- pp 1-7
TLDR
The BioNLP Shared Task 2013 shows advances in the state of the art and demonstrates that extraction methods can be successfully generalized in various aspects.Citations
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Journal ArticleDOI
On Crowd-verification of Biological Networks
Jean Binder,Stéphanie Boué,Anselmo Di Fabio,William Hayes,Julia Hoeng,Anita R. Iskandar,Robin Kleiman,Raquel Norel,Bruce O'Neel,Manuel C. Peitsch,Carine Poussin,Dexter Pratt,Kahn Rhrissorrakrai,Walter K. Schlage,Gustavo Stolovitzky,Marja Talikka +15 more
TL;DR: This article presents a crowd-verification approach for the visualization and expansion of biological networks that will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease.
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COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
Qingyun Wang,Manling Li,Xuan Wang,Nikolaus Nova Parulian,Guangxing Han,Jiawei Ma,Jingxuan Tu,Ying Lin,Haoran Zhang,Weili Liu,Aabhas Chauhan,Yingjun Guan,Bangzheng Li,Ruisong Li,Xiangchen Song,Heng Ji,Jiawei Han,Shih-Fu Chang,James Pustejovsky,Jasmine Rah,David A. Liem,Ahmed Elsayed,Martha Palmer,Clare R. Voss,Cynthia Schneider,Boyan Onyshkevych +25 more
TL;DR: In this paper, a knowledge discovery framework, COVID-KG, was developed to extract fine-grained multimedia knowledge elements (entities, relations and events) from scientific literature.
Biomedical Event Extraction with Machine Learning
TL;DR: This thesis presents a method for automated event extraction, implemented as the Turku Event Extraction System (TEES), capable of detecting binary relations as well as complex event structures.
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Biomedical named entity recognition and linking datasets: survey and our recent development
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Extending the evaluation of Genia Event task toward knowledge base construction and comparison to Gene Regulation Ontology task.
TL;DR: An extended evaluation on all the participating systems in the Genia Event (GE) task is reported, incoporating a KB perspective, and a comparison of the GE and GRO tasks by converting their datasets into each other's format.
References
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Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking
Eugene Charniak,Mark Johnson +1 more
TL;DR: This paper describes a simple yet novel method for constructing sets of 50- best parses based on a coarse-to-fine generative parser that generates 50-best lists that are of substantially higher quality than previously obtainable.
Proceedings ArticleDOI
Overview of BioNLP'09 Shared Task on Event Extraction
TL;DR: The design and implementation of the BioNLP'09 Shared Task is presented, indicating that state-of-the-art performance is approaching a practically applicable level and revealing some remaining challenges.
Performance measures for information extraction
TL;DR: An error measure is defined, the slot error rate, which combines the different types of error directly, without having to resort to precision and recall as preliminary measures.
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PANTHER Pathway: An Ontology-Based Pathway Database Coupled with Data Analysis Tools
Huaiyu Mi,Paul Thomas +1 more
TL;DR: This chapter first discusses how biological knowledge is represented, particularly the importance of ontologies or standards in systems biology research, and uses PANTHER Pathway as an example to illustrate how ontologies and standards play a role in data modeling, data entry, and data display.
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TL;DR: A corpus of discharge summaries annotated with temporal information was provided to be used for the development and evaluation of temporal reasoning systems, and the best systems overwhelmingly adopted a rule based approach for value normalization.