Question answering (QA) on table data is a challenging information retrieval task. This paper describes a QA system for tables created with both machine learning and heuristic tab...
We introduce a probabilistic noisychannel model for question answering and we show how it can be exploited in the context of an end-to-end QA system. Our noisy-channel system outp...
In our system, we make use of Chunk information to analyze the question. A multilevel method is fulfilled to retrieve candidate Bi-sentences. As to answer selecting, we proposed a...
Abstract. Our participation at ResPubliQA 2010 was based on applying an Information Retrieval (IR) engine of high performance and a validation step for removing incorrect answers. ...
In this paper we describe the system we developed for taking part in monolingual Spanish and English tasks at ResPubliQA 2009. Our system was composed by an IR phase focused on im...