Question Answering via Integer Programming over Semi-Structured Knowledge
Table 4: Solver combination results
['Solver', 'Test Score (%)']
This analysis highlights the complementary strengths of these solvers. Following \citeauthoraristo2016 :combining \shortcitearisto2016: combining, we create an ensemble of TableILP, IR, and PMI solvers, combining their answer predictions using a simple Logistic Regression model trained on the development set. This model uses 4 features derived from each solver’s score for each answer option, and 11 features derived from TableILP’s support graphs.