Automated Methods for Extracting and Expanding Lists in Regulatory Text
نویسندگان
چکیده
This is a highly condensed version of a paper [1] that presents automated methods to accurately transform regulations with bulleted lists into sets of complete sentences that include their proper context. We discuss the technical challenges addressed, including extracting intended structure from HTML documents, and correctly distributing preambles over nested text. Our work has been used to preprocess the corpus used for our experiments in classifying paragraphs in regulatory documents by several categories, including illocutionary point, regulation type, and reference structure. That work is presented in a companion paper published in the JURIX 2013 proceedings.
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