{"type":"ScholarlyArticle","title":"ReportParse: A Unified NLP Tool for Extracting Document Structure and Semantics of Corporate Sustainability Reporting","authors":[{"name":"Gaku Morio","slug":"gaku-morio","given":"Gaku","family":"Morio","affiliation":"Stanford University , United States; Hitachi America , United States"},{"name":"Soh Young In","slug":"soh-young-in","given":"Soh Young","family":"In","affiliation":"Korea Advanced Institute of Science and Technology , South Korea"},{"name":"Jungah Yoon","slug":"jungah-yoon","given":"Jungah","family":"Yoon","affiliation":"University of Otago , New Zealand"},{"name":"Harri Rowlands","slug":"harri-rowlands","given":"Harri","family":"Rowlands","affiliation":"InfluenceMap , United Kingdom"},{"name":"Christopher Manning","slug":"christopher-manning","given":"Christopher","family":"Manning","affiliation":"Stanford University , United States"}],"abstract":"We introduce ReportParse, a Python-based tool designed to parse corporate sustainability reports.\r\nIt combines document structure analysis with natural language processing (NLP) models to extract sustainability-related information from the reports.\r\nWe also provide easy-to-use web and command interfaces.\r\nThe tool is expected to aid researchers and analysts in evaluating corporate commitment to and management of sustainability efforts.","doi":"10.24963/ijcai.2024/1024","url":"https://ijcai.org/proceedings/2024/1024","pdf":"https://ijcai.org/proceedings/2024/1024.pdf","markdown":"https://ijcai.org/proceedings/2024/1024.md","bibtex":"https://ijcai.org/proceedings/2024/bibtex/1024","volume":{"slug":"2024","title":"Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2024","url":"https://ijcai.org/proceedings/2024/","year":2024,"location":"Jeju, Korea","dates":"3-9 August 2024","editors":"Kate Larson","isbn":"978-1-956792-04-1","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2024"},"section":"Demo Track","track":"Demo Track","number":1024,"pages":{"first":8749,"last":8753},"keywords":["Natural Language Processing: NLP: Tools","Natural Language Processing: NLP: Applications","Multidisciplinary Topics and Applications: MDA: Social sciences","Multidisciplinary Topics and Applications: MDA: Finance"],"videos":[],"references":[{"position":1,"raw":"[Abid et al., 2019] Abubakar Abid, Ali Abdalla, Ali Abid, Dawood Khan, Abdulrahman Alfozan, and James Zou. 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