Making Document-Level Information Extraction Right for the Right Reasons. (arXiv:2110.07686v2 [cs.CL] UPDATED)

Document-level models for information extraction tasks like slot-filling are
flexible: they can be applied to settings where information is not necessarily
localized in a single sentence. For example, key features of a diagnosis in a
radiology report may not be explicitly stated in one place, but nevertheless
can be inferred from parts of the report's text. However, these models can
easily learn spurious correlations between labels and irrelevant information.
This work studies how to ensure that these models make correct …

arxiv extraction information information extraction making