Interpretable Column Annotation with LLM-Symbolized Decision Process Materialization
arXiv:2607.25228v1 Announce Type: new Abstract: Column annotation (CA), including column type annotation (CTA) and column property annotation (CPA), aims to identify the meanings of table columns and the semantic relationships among them. Recent CA methods usually use various neural models to learn column representations and directly map them to label categories, thereby (1) sacrificing model interpretability and adaptivity, and (2) overlooking rich label semantics and ultimately limiting accura...
arXiv cs.CL
·Mengqi Wang (UNSW Sydney), Jianwei Wang (UNSW Sydney), Qing Liu (Data61, CSIRO), Xiwei Xu (Data61, CSIRO), Zhenchang Xing (Data61, CSIRO), Michael Bain (UNSW Sydney), Liming Zhu (Data61, CSIRO), Wenjie Zhang (UNSW Sydney)
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