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Extracting N-ary Facts from Wikipedia Table Clusters
Proceedings of the 29th ACM International Conference on Information & Knowledge Management
Tables in Wikipedia articles contain a wealth of knowledge that would be useful for many applications if it were structured in a more coherent, queryable form. An important problem is that many of such tables contain the same type of knowledge, but have different layouts and/or schemata. Moreover, some tables refer to entities that we can link to Knowledge Bases (KBs), while others do not. Finally, some tables express entity-attribute relations, while others contain more complex n-arydoi:10.1145/3340531.3412027 dblp:conf/cikm/KruitBU20 fatcat:5sb34ebk7jfsvnxmdyxwy7gyki