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On the unification of syntactic annotations under the Stanford dependency scheme: A case study on BioInfer and GENIA.

, , , , , and . BioNLP@ACL, page 25-32. Association for Computational Linguistics, (2007)

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Building a Large Automatically Parsed Corpus of Finnish., , , , , , and . NODALIDA, volume 85 of Linköping Electronic Conference Proceedings, page 291-300. Linköping University Electronic Press, (2013)Extracting Complex Biological Events with Rich Graph-Based Feature Sets., , , , , and . BioNLP@HLT-NAACL (Shared Task), page 10-18. Association for Computational Linguistics, (2009)PubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations., , , , , , , and . BioNLP@HLT-NAACL, page 82-90. Association for Computational Linguistics, (2012)Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction., , , , and . NoDaLiDa, page 80-85. University of Tartu Library, (2023)Deep Learning, Film History: Model Explanation Techniques in the Analysis of Temporality in Finnish Fiction Film Metadata., , , , and . DHNB, volume 3232 of CEUR Workshop Proceedings, page 50-62. CEUR-WS.org, (2022)Enhancing Universal Dependency Treebanks: A Case Study., , , , , , and . UDW@EMNLP, page 102-107. Association for Computational Linguistics, (2018)UTU: Disease Mention Recognition and Normalization with CRFs and Vector Space Representations., , and . SemEval@COLING, page 807-811. The Association for Computer Linguistics, (2014)Detecting Sequential Genre Change in Eighteenth-Century Texts., , , , , and . CHR, volume 3290 of CEUR Workshop Proceedings, page 243-255. CEUR-WS.org, (2022)All-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning, , , , , and . BMC bioinformatics, 9 (Suppl 11): S2 (2008)Silver Syntax Pre-training for Cross-Domain Relation Extraction., , , , and . ACL (Findings), page 6984-6993. Association for Computational Linguistics, (2023)