Sar-graphs: A Linked Linguistic Knowledge Resource Connecting Facts with Language

Sebastian Krause, Leonhard Hennig, Aleksandra Gabryszak, Feiyu Xu, Hans Uszkoreit

In: Fourth Workshop on Linked Data in Linguistics: Resources and Applications (LDL-2015) at ACL-IJCNLP 2015. Workshop on Linked Data in Linguistics (LDL-2015) 4th located at ACL-IJCNLP 2015 July 31 Beijing China ACL 2015.


We present sar-graphs, a knowledge resource that links semantic relations from factual knowledge graphs to the linguistic patterns with which a language can express instances of these relations. Sar-graphs expand upon existing lexico- semantic resources by modeling syntactic and semantic information at the level of relations, and are hence useful for tasks such as knowledge base population and relation extraction. We present a language-independent method to automatically construct sar-graph instances that is based on distantly supervised relation extraction. We link sar-graphs at the lexical level to BabelNet, WordNet and UBY, and present our ongoing work on pattern- and relation-level linking to FrameNet. An initial dataset of English sar-graphs for 25 relations is made publicly available, together with a Java-based API.


sar_graphs_a_linked_linguistic_knowledge_resource_connecting_facts_with_language_ACL_LDL_2015.pdf (pdf, 921 KB)

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz