Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019

Pankaj Gupta, Usama Yaseen, Hinrich Schütze


Abstract
Named Entity Recognition (NER) and Relation Extraction (RE) are essential tools in distilling knowledge from biomedical literature. This paper presents our findings from participating in BioNLP Shared Tasks 2019. We addressed Named Entity Recognition including nested entities extraction, Entity Normalization and Relation Extraction. Our proposed approach of Named Entities can be generalized to different languages and we have shown it’s effectiveness for English and Spanish text. We investigated linguistic features, hybrid loss including ranking and Conditional Random Fields (CRF), multi-task objective and token level ensembling strategy to improve NER. We employed dictionary based fuzzy and semantic search to perform Entity Normalization. Finally, our RE system employed Support Vector Machine (SVM) with linguistic features. Our NER submission (team:MIC-CIS) ranked first in BB-2019 norm+NER task with standard error rate (SER) of 0.7159 and showed competitive performance on PharmaCo NER task with F1-score of 0.8662. Our RE system ranked first in the SeeDev-binary Relation Extraction Task with F1-score of 0.3738.
Anthology ID:
D19-5720
Volume:
Proceedings of the 5th Workshop on BioNLP Open Shared Tasks
Month:
November
Year:
2019
Address:
Hong Kong, China
Venue:
BioNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
132–142
Language:
URL:
https://aclanthology.org/D19-5720
DOI:
10.18653/v1/D19-5720
Bibkey:
Cite (ACL):
Pankaj Gupta, Usama Yaseen, and Hinrich Schütze. 2019. Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019. In Proceedings of the 5th Workshop on BioNLP Open Shared Tasks, pages 132–142, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019 (Gupta et al., BioNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-5720.pdf
Code
 uyaseen/bionlp-ost-2019
Data
BB