Examples


Description


As in the original paper, we added the possibility to perform question answering using only Quasimodo, i.e. we do not have an underlying language model. We used the same algorithm: Given a question, an answer and a knowledge base, we generate a set of features based on the connections between the words in the knowledge graph. Then, using the same training data as in Quasimodo, we train a linear classifier to predict a score for each answer. We reused the code provided with Quasimodo and added an interface to ask a question and give possible answers. Then, the system provides a score for each answer and displays them.