{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T16:55:04Z","timestamp":1771260904250,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"abstract":"<jats:p>We explore how deep learning methods can be used for contract element extraction. We show that a BILSTM operating on word, POS tag, and token-shape embeddings outperforms the linear sliding-window classifiers of our previous work, without any manually written rules. Further improvements are observed by stacking an additional LSTM on top of the BILSTM, or by adding a CRF layer on top of the BILSTM. The stacked BILSTM-LSTM misclassifies fewer tokens, but the BILSTM-CRF combination performs better when methods are evaluated for their ability to extract entire, possibly multi-token contract elements.<\/jats:p>","DOI":"10.3233\/978-1-61499-838-9-155","type":"book-chapter","created":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:06:08Z","timestamp":1740053168000},"source":"Crossref","is-referenced-by-count":9,"title":["A Deep Learning Approach to Contract Element Extraction"],"prefix":"10.3233","author":[{"family":"Chalkidis Ilias","sequence":"additional","affiliation":[]},{"family":"Androutsopoulos Ion","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,20]],"date-time":"2025-02-20T12:41:59Z","timestamp":1740055319000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-837-2&spage=155&doi=10.3233\/978-1-61499-838-9-155"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-838-9-155","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2017]]}}}