2007 RelExRelationExtractionUsingDep
- (Fundel et al., 2007) ⇒ Katrin Fundel, Robert Küffner, and Ralf Zimmer. (2007). “RelEx- Relation Extraction Using Dependency Parse Trees.” In: Bioinformatics Journal, 23(3). doi:10.1093/bioinformatics/btl616
Subject Headings: RelEx, Relation Extraction System, Dependency Tree.
Notes
- Alternative PDF Link: https://pdfs.semanticscholar.org/5958/114095dacebd3bbed459c9e0f446228e852e.pdf
Cited By
- Google Scholar: ~ 561 Citations (Retrieved 2019-10-13).
- ACM DL: ~ 91 Citations (Retrieved 2019-10-13).
- Semantic Scholar: ~ 361 Citations (Retrieved 2019-10-13).
Quotes
Abstract
Motivation: The discovery of regulatory pathways, signal cascades, metabolic processes or disease models requires knowledge on individual relations like e.g. physical or regulatory interactions between genes and proteins. Most interactions mentioned in the free text of biomedical publications are not yet contained in structured databases.
Results: We developed RelEx, an approach for relation extraction from free text. It is based on natural language preprocessing producing dependency parse trees and applying a small number of simple rules to these trees. We applied RelEx on a comprehensive set of one million MEDLINE abstracts dealing with gene and protein relations and extracted ~150 000 relations with an estimated perfomance of both 80% precision and 80% recall.
Availability: The used natural language preprocessing tools are free for use for academic research. Test sets and relation term lists are available from our website (http://www.bio.ifi.lmu.de/publications/RelEx/).
Contact: katrin.fundel@bio.ifi.lmu.de
References
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2007 RelExRelationExtractionUsingDep | Katrin Fundel Ralf Zimmer Robert Küffner | RelEx---Relation Extraction Using Dependency Parse Trees | 10.1093/bioinformatics/btl616 | 2007 |