Class Cardinality Comparison as a Fermi Problem
This addresses a specific challenge in information retrieval for users needing comparative data, but it is incremental as it builds on existing sources with novel aggregation techniques.
The paper tackled the problem of answering class cardinality comparison questions, such as 'Are there more astronauts or Physics Nobel Laureates?', by aggregating signals from multiple sources for more reliable estimates, achieving an accuracy of 83.7% on a dataset of 4005 class pairs.
Questions on class cardinality comparisons are quite tricky to answer and come with its own challenges. They require some kind of reasoning since web documents and knowledge bases, indispensable sources of information, rarely store direct answers to questions, such as, ``Are there more astronauts or Physics Nobel Laureates?'' We tackle questions on class cardinality comparison by tapping into three sources for absolute cardinalities as well as the cardinalities of orthogonal subgroups of the classes. We propose novel techniques for aggregating signals with partial coverage for more reliable estimates and evaluate them on a dataset of 4005 class pairs, achieving an accuracy of 83.7%.