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Simultaneously Linking Entities and Extracting Relations from Biomedical
  Text Without Mention-level Supervision

Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision

AAAI Conference on Artificial Intelligence (AAAI), 2019
2 December 2019
Trapit Bansal
Pat Verga
Neha Choudhary
Andrew McCallum
ArXiv (abs)PDFHTML

Papers citing "Simultaneously Linking Entities and Extracting Relations from Biomedical Text Without Mention-level Supervision"

4 / 4 papers shown
Title
A Distant Supervision Corpus for Extracting Biomedical Relationships
  Between Chemicals, Diseases and Genes
A Distant Supervision Corpus for Extracting Biomedical Relationships Between Chemicals, Diseases and GenesInternational Conference on Language Resources and Evaluation (LREC), 2022
Dongxu Zhang
Sunil Mohan
M. Torkar
Andrew McCallum
112
13
0
13 Apr 2022
Unsupervised Pre-training for Biomedical Question Answering
Unsupervised Pre-training for Biomedical Question AnsweringConference and Labs of the Evaluation Forum (CLEF), 2020
Vaishnavi Kommaraju
K. Gunasekaran
Kun Li
Trapit Bansal
Andrew McCallum
Ivana Williams
Ana-Maria Istrate
SSLMedIm
143
18
0
27 Sep 2020
Machine Knowledge: Creation and Curation of Comprehensive Knowledge
  Bases
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
Gerhard Weikum
Luna Dong
Simon Razniewski
Fabian M. Suchanek
319
143
0
24 Sep 2020
Neural Entity Linking: A Survey of Models Based on Deep Learning
Neural Entity Linking: A Survey of Models Based on Deep Learning
Ozge Sevgili
Artem Shelmanov
Mikhail V. Arkhipov
Sergey Petrakov
Christian Biemann
VLM3DVAI4TS
473
141
0
31 May 2020
1