Splitting Complex Temporal Questions for Question Answering Systems

Splitting Complex Temporal Questions for Question Answering systems � E. Saquete, P. Mart´ınez-Barco, R. Mu˜noz, J.L. Vicedo Grupo de investigaci´on del Procesamiento del Lenguaje y Sistemas de Informaci´on. Departamento de Lenguajes y Sistemas Inform´aticos. Universidad de Alicante. Alicante, Spain � stela,patricio,rafael,vicedo � @dlsi.ua.es Abstract This paper presents a multi-layered Question An- swering (Q.A.) architecture suitable for enhanc- ing current Q.A. capabilities with the possibility of processing complex questions. That is, questions whose answer needs to be gathered from pieces of factual information scattered in different docu- ments. Specifically, we have designed a layer ori- ented to process the different types of temporal questions. Complex temporal questions are first de- composed into simpler ones, according to the tem- poral relationships expressed in the original ques- tion. In the same way, the answers of each simple ques- tion are re-composed, fulfilling the temporal restric- tions of the original complex question. Using this architecture, a Temporal Q.A. system has been developed. In this paper, we focus on explaining the first part of the process: the decomposition of the complex questions. Furthermore, it has been evaluated with the TERQAS question corpus of 112 temporal ques- tions. For the task of question splitting our system has performed, in terms of precision and recall, 85% and 71%, respectively. 1 Introduction Question Answering could be defined as the pro- cess of computer-answering to precise or arbitrary questions formulated by users. Q.A. systems are es- pecially useful to obtain a specific piece of informa- tion without the need of manually going through all the available documentation related to the topic. Research in Question Answering mainly focuses on the treatment of factual questions. These require as an answer very specific items of data, such as dates, names of entities or quantities, e.g., “What is the capital of Brazil?”. � This paper has been supported by the Spanish government, projects FIT-150500-2002-244, FIT-150500-2002-416, TIC- 2003-07158-C04-01 and TIC2000-0664-C02-02. Temporal Q.A. is not a trivial task due to the com- plexity temporal questions may reach. Current op- erational Q.A. systems can deal with simple factual temporal questions. That is, questions requiring to be answered with a date, e.g. “When did Bob Mar- ley die?”. or questions that include simple temporal expressions in their formulation, e.g., “Who won the U.S. Open in 1999?”. Processing this sort of ques- tions is usually performed by identifying explicit temporal expressions in questions and relevant doc- uments, in order to gather the necessary information to answer the queries. Even though, it seems necessary to emphasize that the system described in (Breck et al., 2000) is the only one also using implicit temporal expression recognition for Q.A. purposes. It does so by apply- ing the temporal tagger developed by Mani and Wil- son (2000). However, issues like addressing the temporal properties or the ordering of events in questions, re- main beyond the scope of current Q.A. systems: � “Who was spokesman of the Soviet Embassy in Baghdad during the invasion of Kuwait?” � “Is Bill Clinton currently the President …

Content truncated to 500 words