Automated regulatory compliance checking requires automated information extraction (IE) from regulatory textual documents (e.g. building codes). Automated IE is a challenging task that requires complex processing of text. Natural Language Processing (NLP) aims at enabling computers to process natural language text in a human-like manner using a variety of text processing techniques, such as phrase-structure parsing, dependency parsing, etc. This paper proposes a hybrid syntactic (syntax/grammar-related) and semantic (meaning/context-related) NLP approach for automated IE from construction regulatory documents, and explores the use of two techniques (phrase-structure grammar and dependency grammar) for extracting information from complex sentences. IE rules were developed based on Chapter 12 of the 2006 International Building Code; and the approach was tested on Chapter 12 of the 2009 International Fire Code. Initial experimental results are presented, empirically evaluated in terms of precision and recall, and discussed.
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Zhang et al. (2012) studied this question.