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Using Rhetorical Structure Theory and Entity Grids to Automatically Evaluate Local Coherence in Texts.

, , and . PROPOR, volume 8775 of Lecture Notes in Computer Science, page 232-243. Springer, (2014)

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A Discursive Grid Approach to Model Local Coherence in Multi-document Summaries., and . SIGDIAL Conference, page 60-67. The Association for Computer Linguistics, (2015)Threshold-Based Classification to Enhance Confidence in Open Set of Legal Texts., , , , , , and . IDEAL, volume 14404 of Lecture Notes in Computer Science, page 269-280. Springer, (2023)Enriching entity grids and graphs with discourse relations: the impact in local coherence evaluation., and . STIL, page 151-160. Sociedade Brasileira de Computação, (2015)UlyssesNER-Br: A Corpus of Brazilian Legislative Documents for Named Entity Recognition., , , , , , , , , and 9 other author(s). PROPOR, volume 13208 of Lecture Notes in Computer Science, page 3-14. Springer, (2022)Using Rhetorical Structure Theory and Entity Grids to Automatically Evaluate Local Coherence in Texts., , and . PROPOR, volume 8775 of Lecture Notes in Computer Science, page 232-243. Springer, (2014)Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification., , , , , , and . HAIS, volume 14001 of Lecture Notes in Computer Science, page 108-120. Springer, (2023)Building a Language Model for Local Coherence in Multi-document Summaries Using a Discourse-Enriched Entity-Based Model., , and . BRACIS, page 44-49. IEEE Computer Society, (2014)A Qualitative Analysis of a Corpus of Opinion Summaries based on Aspects., , , , , , , , , and 3 other author(s). LAW@NAACL-HLT, page 62-71. The Association for Computer Linguistics, (2015)The Coreference Annotation of the CSTNews Corpus., , , , , , , , , and 6 other author(s). IberEval@SEPLN, volume 1881 of CEUR Workshop Proceedings, page 102-112. CEUR-WS.org, (2017)Natural Language Processing Application in Legislative Activity: a Case Study of Similar Amendments in the Brazilian Senate., , , , , , , and . PROPOR, page 614-619. Association for Computational Lingustics, (2024)