Cross-Lingual Question Answering Using Common Semantic Space

With the advent of Big Data concept, a lot of attention has been paid to structuring and giving semantic to this data. Knowledge bases like DBPedia play an important role to achieve this goal. Question answering systems are common approach to address expressivity and usability of information extraction from knowledge bases. Recent researches focused only on monolingual QA systems while cross-lingual setting has still so many barriers. In this paper we introduce a new cross-lingual approach using a unified semantic space among languages. After keyword extraction, entity linking and answer type detection, we use cross lingual semantic similarity to extract the answer from knowledge base via relation selection and type matching. We have evaluated our approach on Persian and Spanish which are typologically different languages. Our experiments are on DBPedia. The results are promising for both languages.