Bulgarian Question Answering for Machine Reading.
Kiril Simov, Petya Osenova, Georgi Georgiev, Valentin Zhikov, Laura Toloşi · 2012
participating for QA4MRE task for Bulgarian. The system represented in the paper exploits an NLP Pipeline for Bulgarian in order to process the questions, answers and the supporting texts. Then we represent the results of the analysis as a bag of linguistic units- lemmas, dependency relations. These bags of words are the match between the question plus answer and the sentences in the text. The answer that maximizes the overlap is selected as the correct one. Since the system is deterministic we have only one run. The score achieved by the run is 0.29. The other two runs are performed as baseline runs with randomly selected answers. Their scores are 0.20 and 0.12, respectively. Thus, the using of linguistic units in the overlapping estimation provides significant improvements over the baseline.