Entity Retrieval for Answering Entity-Centric Questions
This addresses a specific bottleneck in retrieval-augmented question answering for entity-centric queries, offering an incremental improvement over existing methods.
The paper tackled the problem of retrieving documents for entity-centric questions by proposing Entity Retrieval, which uses salient entities in the question instead of question-document similarity, resulting in more accurate answers and improved efficiency.
The similarity between the question and indexed documents is a crucial factor in document retrieval for retrieval-augmented question answering. Although this is typically the only method for obtaining the relevant documents, it is not the sole approach when dealing with entity-centric questions. In this study, we propose Entity Retrieval, a novel retrieval method which rather than relying on question-document similarity, depends on the salient entities within the question to identify the retrieval documents. We conduct an in-depth analysis of the performance of both dense and sparse retrieval methods in comparison to Entity Retrieval. Our findings reveal that our method not only leads to more accurate answers to entity-centric questions but also operates more efficiently.