RelEx -: Relation extraction using dependency parse trees
RelEx -: Relation extraction using dependency parse trees
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DOI：
10.1093/bioinformatics/btl616
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发表时间：
2007-02-01
期刊：
影响因子：
5.8
通讯作者：
Zimmer, Ralf
中科院分区：
文献类型：
--
作者：
Fundel, Katrin;Kueffner, Robert;Zimmer, Ralf
动机：发现调控途径、信号级联、代谢过程或疾病模型需要了解个体关系，例如基因和蛋白质之间的物理或调控相互作用。结果：我们开发了一种从自由文本中提取关系的方法Relex。它基于自然语言的预处理，生成依存关系分析树，并对这些树应用少量的简单规则。我们使用Relex对一百万个涉及基因和蛋白质关系的MEDLINE摘要进行了综合处理，提取了15万个关系，估计准确率和召回率都达到了80%。可用性：使用的自然语言预处理工具可以免费用于学术研究。测试集和关系术语列表可从我们的website(http://www.bioifiImu.de/publications/RElEx/).获得
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.bioifiImu.de/publications/RElEx/).