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Tackling the Challenge of Computational Identification of Characters in Fictional Narratives.

, , and . ICCC, page 122-129. IEEE, (2019)

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A Multilingual Multi-domain Data-to-Text Natural Language Generation Approach., and . Proces. del Leng. Natural, (2017)NATSUM: Narrative abstractive summarization through cross-document timeline generation., , , and . Inf. Process. Manag., 56 (5): 1775-1793 (2019)Inflection Generation for Spanish Verbs using Supervised Learning., , and . SWCN@EMNLP, page 136-141. Association for Computational Linguistics, (2017)Tackling the Challenge of Computational Identification of Characters in Fictional Narratives., , and . ICCC, page 122-129. IEEE, (2019)HanaNLG: A Flexible Hybrid Approach for Natural Language Generation., and . CICLing (2), volume 13452 of Lecture Notes in Computer Science, page 507-519. Springer, (2019)Generating sets of related sentences from input seed features., and . WebNLG, page 1-4. Association for Computational Linguistics, (2016)Statistical language modelling for automatic story generation., , and . J. Intell. Fuzzy Syst., 34 (5): 3069-3079 (2018)To what extent does content selection affect surface realization in the context of headline generation?, , and . Comput. Speech Lang., (2021)A Study on Flexibility in Natural Language Generation Through a Statistical Approach to Story Generation., , and . NLDB, volume 10260 of Lecture Notes in Computer Science, page 492-498. Springer, (2017)Applying Natural Language Processing Techniques to Generate Open Data Web APIs Documentation., , , , , and . ICWE, volume 12128 of Lecture Notes in Computer Science, page 416-432. Springer, (2020)