Query Symbolically or Retrieve Semantically? A Dataset and Method for Semi-Structured Question Answering

arXiv:2605.27164v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems for question answering typically retrieve evidence by semantic similarity between the query and document chunks. While effective for unstructured text, this approach is less reliable on semi-structured corpora where answering may require exact filtering, aggregation, or exhaustive retrieval over structured attributes across multiple documents. Symbolic approaches support such operations, but they are often brittle on noisy natural-language corpora. We address this gap with DualGraph, a RAG framework th

Source: arXiv cs.AI — read the full report at the original publisher.

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