Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering
Table 4: Effects of different relation types in GraphReader. We compare input graphs containing different sets of edges, where we use GraphRetriever and GraphReader (binary).
['[EMPTY]', '[BOLD] WebQuestions', '[BOLD] Natural Q']
cross-doc, which only includes edges between passages according to the Wikidata relations, (d) inner-doc, which only includes child and parent, and (e) cross+inner, which includes both cross-doc and inner-doc, corresponding to the graph constructed by our approach. Results indicate that cross-doc and inner-doc relations achieve good performance across two datasets. In particular, using relation information is better than ignoring relation information (fully connected, empty), demonstrating the importance of selecting a good set of graph edges.