Entity Retrieval for Answering Entity-Centric Questions
August 05, 2024 Β· Declared Dead Β· π Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing
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Authors
Hassan S. Shavarani, Anoop Sarkar
arXiv ID
2408.02795
Category
cs.IR: Information Retrieval
Cross-listed
cs.CL
Citations
8
Venue
Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing
Last Checked
4 months ago
Abstract
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.
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