Abstract
The National Environmental Policy Act (NEPA) provides a trove of data on how environmental policy decisions have been made in the United States over the last 50 years. Unfortunately, there is no central database for this information and it is too voluminous to assess manually. We describe our efforts to enable systematic research over US environmental policy by extracting and organizing metadata from the text of NEPA documents. Our contributions include collecting more than 40,000 NEPA-related documents, and evaluating rule-based baselines that establish the difficulty of three important tasks: Identifying lead agencies, aligning document versions, and detecting reused text.
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CITATION STYLE
Bethard, S., Laparra, E., Wang, S., Zhao, Y., Al-Ghezi, R., Lien, A., & López-Hoffman, L. (2019). Inferring missing metadata from environmental policy texts. In LaTeCH@NAACL-HLT 2019 - 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings (pp. 46–51). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w19-2506
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