Abstract
This paper evaluates the impact of various event extraction systems on automatic pathway curation using the popular mTOR pathway. We quantify the impact of training data sets as well as different machine learning classifiers and show that some improve the quality of automatically extracted pathways.- Anthology ID:
- W17-2331
- Volume:
- BioNLP 2017
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada,
- Venue:
- BioNLP
- SIG:
- SIGBIOMED
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 247–256
- Language:
- URL:
- https://aclanthology.org/W17-2331
- DOI:
- 10.18653/v1/W17-2331
- Cite (ACL):
- Wojciech Kusa and Michael Spranger. 2017. External Evaluation of Event Extraction Classifiers for Automatic Pathway Curation: An extended study of the mTOR pathway. In BioNLP 2017, pages 247–256, Vancouver, Canada,. Association for Computational Linguistics.
- Cite (Informal):
- External Evaluation of Event Extraction Classifiers for Automatic Pathway Curation: An extended study of the mTOR pathway (Kusa & Spranger, BioNLP 2017)
- PDF:
- https://preview.aclanthology.org/auto-file-uploads/W17-2331.pdf
- Code
- sbnlp/2017BioNLPEvaluation