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Annotating Event Appearance for Japanese Chess Commentary Corpus.

, and . LREC, page 4302-4308. European Language Resources Association, (2020)

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Japanese Event Factuality Analysis in the Era of BERT., , , and . IEEE Access, (2023)Can Symbol Grounding Improve Low-Level NLP? Word Segmentation as a Case Study., , and . EMNLP, page 2298-2303. The Association for Computational Linguistics, (2015)Texylon: Dataset of Log-to-Description and Description-to-Log Generation for Text Analytics Tools., , , and . JSAI-isAI, volume 14741 of Lecture Notes in Computer Science, page 269-283. Springer, (2024)Recipe Generation from Unsegmented Cooking Videos., , , , and . CoRR, (2022)Deep Reinforcement Learning with Hidden Layers on Future States., , , and . CGW@IJCAI, volume 818 of Communications in Computer and Information Science, page 46-60. Springer, (2017)Automatic Construction of a Large-Scale Corpus for Geoparsing Using Wikipedia Hyperlinks., , , , and . LREC/COLING, page 1883-1888. ELRA and ICCL, (2024)Annotating Event Appearance for Japanese Chess Commentary Corpus., and . LREC, page 4302-4308. European Language Resources Association, (2020)Learning a game commentary generator with grounded move expressions., , and . CIG, page 177-184. IEEE, (2015)Annotating Modality Expressions and Event Factuality for a Japanese Chess Commentary Corpus., , , and . LREC, European Language Resources Association (ELRA), (2018)State-aware Video Procedural Captioning., , , , and . ACM Multimedia, page 1766-1774. ACM, (2021)