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attribute-recommendation

topic1 events
papersTODAY 04:00 UTC

TEAR: LLM prompting approach extracts tables from text with attribute recommendation

A new arXiv paper introduces TEAR, a method that uses instruction-prompted large language models to pull tabular data out of unstructured text. The approach adds attribute recommendation, meaning the system suggests which columns or fields the extracted data should be organized under. The authors note that prior prompting-based work has generally assumed a fixed input setup, which TEAR aims to move beyond.

llm/table-extraction/information-extraction/arxiv