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For the task of question answering (QA) over Freebase on the WEBQUESTIONS dataset Thus we turned this task into slot-filling for tuples: predicting relations to get answers given a question's topic. We design efficient data structures to identify question topics organically from 46 million Freebase topic names, without employing any NLP processing tools. Then we present a lean QA system that runs in real time (in offline batch testing it answered two thousand questions in 51 seconds on a laptop). The system also achieved 7.8% better F 1 score (harmonic mean of average precision and recall) than the previous state of the art.
Xuchen Yao (Thu,) studied this question.
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