Towards an Argument Mining Pipeline Transforming Texts to Argument Graphs
Table 3: Accuracy of the relation type classification models.
['[BOLD] Language', '[BOLD] LG', '[BOLD] KNN', '[BOLD] RF', '[BOLD] XGB']
The training of the relationship type model has been performed using the Kialo dataset due to the large number of available relations. The data was transformed into triples x,y,z with x, z being I-nodes y being the S-node connected via edges to them. We used models of type logistic regression (LG), k-nearest neighbors (KNN), random forest (RF) and gradient boosting (XGB) for the German and English languages. XGB achieved the highest accuracy for both languages.