BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences. (26th February 2017)
- Record Type:
- Journal Article
- Title:
- BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences. (26th February 2017)
- Main Title:
- BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences
- Authors:
- Ravikumar, K.E.
Rastegar-Mojarad, Majid
Liu, Hongfang - Abstract:
- Abstract: Extracting meaningful relationships with semantic significance from biomedical literature is often a challenging task. BioCreative V track4 challenge for the first time has organized a comprehensive shared task to test the robustness of the text-mining algorithms in extracting semantically meaningful assertions from the evidence statement in biomedical text. In this work, we tested the ability of a rule-based semantic parser to extract Biological Expression Language (BEL) statements from evidence sentences culled out of biomedical literature as part of BioCreative V Track4 challenge. The system achieved an overall best F-measure of 21.29% in extracting the complete BEL statement. For relation extraction, the system achieved an F-measure of 65.13% on test data set. Our system achieved the best performance in five of the six criteria that was adopted for evaluation by the task organizers. Lack of ability to derive semantic inferences, limitation in the rule sets to map the textual extractions to BEL function were some of the reasons for low performance in extracting the complete BEL statement. Post shared task we also evaluated the impact of differential NER components on the ability to extract BEL statements on the test data sets besides making a single change in the rule sets that translate relation extractions into a BEL statement. There is a marked improvement by over 20% in the overall performance of the BELMiner's capability to extract BEL statement on the testAbstract: Extracting meaningful relationships with semantic significance from biomedical literature is often a challenging task. BioCreative V track4 challenge for the first time has organized a comprehensive shared task to test the robustness of the text-mining algorithms in extracting semantically meaningful assertions from the evidence statement in biomedical text. In this work, we tested the ability of a rule-based semantic parser to extract Biological Expression Language (BEL) statements from evidence sentences culled out of biomedical literature as part of BioCreative V Track4 challenge. The system achieved an overall best F-measure of 21.29% in extracting the complete BEL statement. For relation extraction, the system achieved an F-measure of 65.13% on test data set. Our system achieved the best performance in five of the six criteria that was adopted for evaluation by the task organizers. Lack of ability to derive semantic inferences, limitation in the rule sets to map the textual extractions to BEL function were some of the reasons for low performance in extracting the complete BEL statement. Post shared task we also evaluated the impact of differential NER components on the ability to extract BEL statements on the test data sets besides making a single change in the rule sets that translate relation extractions into a BEL statement. There is a marked improvement by over 20% in the overall performance of the BELMiner's capability to extract BEL statement on the test set. The system is available as a REST-API at http://54.146.11.205:8484/BELXtractor/finder/ Database URL: http://54.146.11.205:8484/BELXtractor/finder/ … (more)
- Is Part Of:
- Database. Volume 2017(2017)
- Journal:
- Database
- Issue:
- Volume 2017(2017)
- Issue Display:
- Volume 2017, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 2017
- Issue:
- 2017
- Issue Sort Value:
- 2017-2017-2017-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-02-26
- Subjects:
- Biology -- Databases -- Periodicals
Bioinformatics -- Periodicals
570.285 - Journal URLs:
- http://database.oxfordjournals.org/ ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/database/baw156 ↗
- Languages:
- English
- ISSNs:
- 1758-0463
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12244.xml