{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T05:23:53Z","timestamp":1733462633930,"version":"3.30.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685625","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,5]],"date-time":"2024-12-05T00:00:00Z","timestamp":1733356800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,5]]},"abstract":"<jats:p>Legal Question Answering (LQA) systems are facing a wide range of challenges. Deep learning-based methods need to be improved to better perform on the underlying logical reasoning tasks. We propose a hybrid neurosymbolic framework to achieve this, by enhancing the pretraining of BERT based models with LogicQA and the integration of PyReason.<\/jats:p>","DOI":"10.3233\/faia241271","type":"book-chapter","created":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:01:20Z","timestamp":1733443280000},"source":"Crossref","is-referenced-by-count":0,"title":["Legal Question Answering Based on Logical Reasoning in Large Pretrained Language Models"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3582-9690","authenticated-orcid":false,"given":"Joseph","family":"Dimos","sequence":"first","affiliation":[{"name":"AxiomaVox"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1094-6374","authenticated-orcid":false,"given":"Eva","family":"Fourel","sequence":"additional","affiliation":[{"name":"AxiomaVox"},{"name":"University of Paris Nanterre - Centre de Th\u00e9orie et d\u2019Analyse du Droit"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Legal Knowledge and Information Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241271","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,6]],"date-time":"2024-12-06T00:01:20Z","timestamp":1733443280000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241271"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,5]]},"ISBN":["9781643685625"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241271","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,5]]}}}