Journal
WEB CONFERENCE 2020: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WWW 2020)
Volume -, Issue -, Pages 1205-1216Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3366423.3380197
Keywords
Free-Text Knowledge Graph; Factoid Question Answering; Graph Neural Network
Funding
- NSF [IIS-1748663, IIS-1822494]
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We introduce DELFT, a factoid question answering system which combines the nuance and depth of knowledge graph question answering approaches with the broader coverage of free-text. DELFT builds a free-text knowledge graph from Wikipedia, with entities as nodes and sentences in which entities co-occur as edges. For each question, DELFT finds the subgraph linking question entity nodes to candidates using text sentences as edges, creating a dense and high coverage semantic graph. A novel graph neural network reasons over the free-text graph-combining evidence on the nodes via information along edge sentences-to select a final answer. Experiments on three question answering datasets show DELFT can answer entity-rich questions better than machine reading based models, BERT-based answer ranking and memory networks. DELFT' s advantage comes from both the high coverage of its free-text knowledge graph-more than double that of DBpedia relations-and the novel graph neural network which reasons on the rich but noisy free-text evidence.
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