Answering Complex Open-domain Questions Through Iterative Query Generation
Table 7: IR performance (recall in percentages) of various Elasticsearch setups on the HotpotQA dev set using the original question.
['[BOLD] IR System', '[BOLD] R@10 for  [ITALIC] d1', '[BOLD] R@10 for  [ITALIC] d2']
To this end, we propose to rerank these query results with a simple but effective heuristic that alleviates this issue. We would first retrieve at least 50 candidate documents for each query for consideration, and boost the query scores of documents whose title exactly matches the search query, or is a substring of the search query. Specifically, we multiply the document score by a heuristic constant between 1.05 and 1.5, depending on how well the document title matches the query, before reranking all search results. This results in a significant improvement in these cases. For the query “George W. Bush”, the page for the former US president is ranked at the top after reranking.