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CoMeT: Integrating different levels of linguistic modeling for meaning assessment.

, , , and . SemEval@NAACL-HLT, page 608-616. The Association for Computer Linguistics, (2013)

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Evaluating Answers to Reading Comprehension Questions in Context: Results for German and the Role of Information Structure., , , and . TextInfer@EMNLP, page 1-9. Association for Computational Linguistics, (2011)Short Answer Assessment: Establishing Links Between Research Strands., , and . BEA@NAACL-HLT, page 190-200. The Association for Computer Linguistics, (2012)978-1-937284-20-6.CoMiC: Adapting a Short Answer Assessment System for Answer Selection., and . SemEval@NAACL-HLT, page 247-251. The Association for Computer Linguistics, (2015)Focus Annotation of Task-based Data: A Comparison of Expert and Crowd-Sourced Annotation in a Reading Comprehension Corpus., , and . LREC, European Language Resources Association (ELRA), (2016)Automatic Focus Annotation: Bringing Formal Pragmatics Alive in Analyzing the Information Structure of Authentic Data., and . NAACL-HLT, page 117-128. Association for Computational Linguistics, (2018)Focus Annotation in Reading Comprehension Data., and . LAW@COLING, page 159-168. The Association for Computer Linguistics, (2014)Is getting the right answer just about choosing the right words? The role of syntactically-informed features in short answer scoring., , , , , , , , , and 3 other author(s). CoRR, (2014)CoMeT: Integrating different levels of linguistic modeling for meaning assessment., , , and . SemEval@NAACL-HLT, page 608-616. The Association for Computer Linguistics, (2013)Focus Annotation of Task-based Data: Establishing the Quality of Crowd Annotation., , and . LAW@ACL, The Association for Computer Linguistics, (2016)Generating Feedback for English Foreign Language Exercises., , , , , and . BEA@NAACL-HLT, page 127-136. Association for Computational Linguistics, (2018)