Semantic Graphs for Generating Deep Questions Liangming Pan1;2 Yuxi Xie3 Yansong Feng3 Tat-Seng Chua2 Min-Yen Kan2 1NUS Graduate School for Integrative Sciences and Engineering 2School of Computing, National University of Singapore, Singapore 3Wangxuan Institute of Computer Technology, Peking University
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[email protected] Input Sentence: Abstract Oxygen is used in cellular respiration and released by photosynthesis, which uses the energy of sunlight to produce oxygen from water. Question: What life process produces oxygen in the presence of light? This paper proposes the problem of Deep Answer: Photosynthesis Question Generation (DQG), which aims to a) Example of Shallow Question Generation Input Paragraph A: Pago Pago International Airport generate complex questions that require rea- Pago Pago International Airport, also known as Tafuna Airport, is a public airport soning over multiple pieces of information of located 7 miles (11.3 km) southwest of the central business district of Pago Pago, in the village and plains of Tafuna on the island of Tutuila in American Samoa, an the input passage. In order to capture the unincorporated territory of the United States. Input Paragraph B: Hoonah Airport global structure of the document and facil- Hoonah Airport is a state-owned public-use airport located one nautical mile (2 km) southeast of the central business district of Hoonah, Alaska. itate reasoning, we propose a novel frame- Question: Are Pago Pago International Airport and Hoonah Airport both on work which first constructs a semantic-level American territory? Answer: Yes graph for the input document and then en- b) Example of Deep Question Generation codes the semantic graph by introducing an attention-based GGNN (Att-GGNN).