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NotaryPedia: A Knowledge Graph of Historical Notarial Manuscripts

机译:公证人:历史公证手稿的知识图

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摘要

The Notarial Archives in Valletta, the capital city of Malta, houses a rich and valuable collection of around twenty thousand notarial manuscripts dating back to the 15th century. The Archive wants to make the contents of this collection easily accessible and searchable to researchers and the general public. Knowledge Graphs have been successfully used to represent similar historical content. Nevertheless, building a Knowledge Graph for the archives is challenging as these documents are written in medieval Latin and currently there is a lack of information extraction tools that recognise this language. This is, furthermore, compounded with a lack of medieval Latin corpora to train and evaluate machine learning algorithms, as well as a lack of an ontological representation for the contents of notarial manuscripts. In this paper, we present NotaryPedia, a Knowledge Graph for the Notarial Archives. We extend our previous work on entity and keyphrase extraction with relation extraction to populate the Knowledge Graph using an ontological vocabulary for notarial deeds. Furthermore, we perform Knowledge Graph completeness using link-prediction and inference. Our work was evaluated using different translational distance and semantic matching models to predict relations amongst literals by promoting them to entities and to infer new knowledge from existing entities. A 49% relation prediction accuracy using TransE was achieved.
机译:马耳他首都瓦莱塔的公证档案馆藏有丰富而有价值的收藏,可追溯到15世纪,大约有2万份公证手稿。档案馆希望使研究人员和公众可以轻松访问和搜索该馆藏的内容。知识图已成功用于表示相似的历史内容。然而,由于这些文档是用中世纪的拉丁语编写的,因此为这些文档构建知识图很有挑战性,并且目前缺乏识别该语言的信息提取工具。此外,这还加上缺乏中世纪的拉丁语料库来训练和评估机器学习算法,以及缺少公证手稿内容的本体表示。在本文中,我们介绍了NotaryPedia(公证档案的知识图)。我们将先前关于实体和关键字短语提取以及关系提取的工作扩展为使用用于公证行为的本体词汇填充知识图。此外,我们使用链接预测和推理来执行知识图完整性。我们使用不同的翻译距离和语义匹配模型对我们的工作进行了评估,以通过将文字提升为实体并从现有实体中推断出新知识来预测文字之间的关系。使用TransE可以达到49%的关系预测精度。

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