Extraction, analysis and representation of imperfect conditional and causal sentences by means of a semi-automatic process

Causality is not only a matter of causal statements, but also of conditional sentences. In conditional statements, causality generally emerges from the entailment relationship between the antecedent and the consequence. This entailment is frequently vague and uncertain in nature. In this article, we present a method of retrieving crisp and imperfect conditional and causal sentences identified by some linguistic patterns. These sentences are pre-processed to obtain both single cause-effect structures and causal chains. The result is displayed automatically in an imperfect causal graph by means of a Java application. The causal graph shows the strenght of the causal link labelling it with a fuzzy quantifier and the intensity of the cause or effect nodes with linguistics hedges. The knowledge base used to provide automatic information based on causal relations was some medical texts, suited for the described process.