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A Survey on Open Information Extraction from Rule-based Model to Large Language Model
April 17, 2024, 4:46 a.m. | Pai Liu, Wenyang Gao, Wenjie Dong, Lin Ai, Ziwei Gong, Songfang Huang, Zongsheng Li, Ehsan Hoque, Julia Hirschberg, Yue Zhang
cs.CL updates on arXiv.org arxiv.org
Abstract: Open information extraction is an important NLP task that targets extracting structured information from unstructured text without limitations on the relation type or the domain of the text. This survey paper covers open information extraction technologies from 2007 to 2022 with a focus on new models not covered by previous surveys. We propose a new categorization method from the source of information perspective to accommodate the development of recent OIE technologies. In addition, we summarize …
abstract arxiv cs.cl domain extraction information information extraction language language model large language large language model limitations nlp paper survey targets technologies text type unstructured
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