Table-based Question Answering

Table-based Question Answering is an important subtask in natural language processing, aimed at parsing and understanding structured data tables to accurately answer natural language questions posed by users. The goal of this task is to extract relevant information from the table and generate precise and meaningful answers. Its application value is extensive, including but not limited to data analysis, intelligent assistants, and corporate information systems, effectively enhancing the efficiency and accuracy of data querying and utilization.