Cause and Effect Extraction from Biomedical Corpus

Abstract

The objective of the present work is to automatically extract the cause and effect from discourse analyzed biomedical corpus. Cause-effect is defined as a relation established between two events, where first event acts as the cause of second event and the second event is the effect of first event. Any causative constructions need three components, a causal marker, cause and effect. In this study, we consider the automatic extraction of cause and effect realized by explicit discourse connective markers. We evaluated our system using BIONLP/NLPBA 2004 shared task test data and obtained encouraging results.