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Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings.

, , , , and . ACL (1), page 5740-5753. Association for Computational Linguistics, (2019)

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Evaluating Learning Language Representations., , , , , , , , , and . CLEF, volume 9283 of Lecture Notes in Computer Science, page 254-260. Springer, (2015)A Question Answering System for German. Experiments with Morphological Linguistic Resources., , and . LREC, European Language Resources Association, (2008)Improving Citation Polarity Classification with Product Reviews., and . ACL (2), page 42-48. The Association for Computer Linguistics, (2014)Part-of-Speech Tagging using a Variable Memory Markov Model., and . ACL, page 181-187. Morgan Kaufmann Publishers / ACL, (1994)SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference., and . ACL (1), page 902-914. Association for Computational Linguistics, (2019)Learning Word Meta-Embeddings., and . ACL (1), The Association for Computer Linguistics, (2016)Active Learning with Amazon Mechanical Turk., , and . EMNLP, page 1546-1556. ACL, (2011)Unlabeled Data for Morphological Generation With Character-Based Sequence-to-Sequence Models., and . SWCN@EMNLP, page 76-81. Association for Computational Linguistics, (2017)Efficient Higher-Order CRFs for Morphological Tagging., , and . EMNLP, page 322-332. ACL, (2013)A Comparison of Classifiers and Document Representations for the Routing Problem., , and . SIGIR, page 229-237. ACM Press, (1995)