Implementing RAG presents a challenge, especially when it comes to effectively parsing and understanding tables in unstructured documents. This is particularly difficult with scanned documents or documents in image format. There are at least three aspects of these challenges:

• The complexity of scanning documents or image documents, such as their diverse structures, the inclusion of non-text elements, and the combination of handwritten and printed content, presents challenges for accurately extracting table information automatically. Inaccurate parsing can damage the table structure, and using an incomplete table for embedding can not only fail to capture the table’s semantic information, but it can also easily corrupt the RAG results.
• How to extract table captions and effectively link them to their respective tables.
• How to design an index structure to effectively store the semantic information of the table.

This article begins by introducing the key technologies for managing tables in RAG. It then reviews some existing open-source solutions before proposing and implementing a new solution.

key Technologies

Table Parsing

The primary function of this module is to accurately extract the table structure from unstructured documents or…