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Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions.

, , and . TextGraphs@EMNLP, page 90-100. Association for Computational Linguistics, (2019)

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Investigating Expressiveness of Transformer in Spectral Domain for Graphs., , , , , and . CoRR, (2022)Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models., , , , , and . CIKM, page 2157-2160. ACM, (2020)How Expressive are Transformers in Spectral Domain for Graphs?, , , , , and . Trans. Mach. Learn. Res., (2022)Old is Gold: Linguistic Driven Approach for Entity and Relation Linking of Short Text., , , , , , and . NAACL-HLT (1), page 2336-2346. Association for Computational Linguistics, (2019)Sparsity-based Feature Selection for Anomalous Subgroup Discovery., , , , , , , and . CoRR, (2022)Ranking Facts for Explaining Answers to Elementary Science Questions., , and . CoRR, (2021)Matching Natural Language Relations to Knowledge Graph Properties for Question Answering., , and . SEMANTiCS, page 89-96. ACM, (2017)KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction., , , , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 535-548. Association for Computational Linguistics, (2021)Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking., , , , , and . WISE (1), volume 12342 of Lecture Notes in Computer Science, page 328-342. Springer, (2020)Knowledge Context for Entity and Relation Linking.. University of Bonn, Germany, (2021)