Inferring missing metadata from environmental policy texts

Steven Bethard, Egoitz Laparra, Sophia Wang, Yiyun Zhao, Ragheb Al-Ghezi, Aaron Lien, Laura López-Hoffman

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.
Anthology ID:
W19-2506
Volume:
Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
Month:
June
Year:
2019
Address:
Minneapolis, USA
Editors:
Beatrice Alex, Stefania Degaetano-Ortlieb, Anna Kazantseva, Nils Reiter, Stan Szpakowicz
Venue:
LaTeCH
SIG:
SIGHUM
Publisher:
Association for Computational Linguistics
Note:
Pages:
46–51
Language:
URL:
https://aclanthology.org/W19-2506
DOI:
10.18653/v1/W19-2506
Bibkey:
Cite (ACL):
Steven Bethard, Egoitz Laparra, Sophia Wang, Yiyun Zhao, Ragheb Al-Ghezi, Aaron Lien, and Laura López-Hoffman. 2019. Inferring missing metadata from environmental policy texts. In Proceedings of the 3rd Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 46–51, Minneapolis, USA. Association for Computational Linguistics.
Cite (Informal):
Inferring missing metadata from environmental policy texts (Bethard et al., LaTeCH 2019)
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PDF:
https://preview.aclanthology.org/ingest-2024-clasp/W19-2506.pdf
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