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

, , и . PROPOR, том 8775 из Lecture Notes in Computer Science, стр. 232-243. Springer, (2014)

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Gustavo Henrique de Souza Dias

Geraldo Souza Dias

Philippe De Souza

Márcio Noveli

Márcio Rosa D'Avila

 

Другие публикации лиц с тем же именем

UlyssesNER-Br: A Corpus of Brazilian Legislative Documents for Named Entity Recognition., , , , , , , , , и 9 other автор(ы). PROPOR, том 13208 из Lecture Notes in Computer Science, стр. 3-14. Springer, (2022)Enriching entity grids and graphs with discourse relations: the impact in local coherence evaluation., и . STIL, стр. 151-160. Sociedade Brasileira de Computação, (2015)Using Rhetorical Structure Theory and Entity Grids to Automatically Evaluate Local Coherence in Texts., , и . PROPOR, том 8775 из Lecture Notes in Computer Science, стр. 232-243. Springer, (2014)Building a Language Model for Local Coherence in Multi-document Summaries Using a Discourse-Enriched Entity-Based Model., , и . BRACIS, стр. 44-49. IEEE Computer Society, (2014)Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification., , , , , , и . HAIS, том 14001 из Lecture Notes in Computer Science, стр. 108-120. Springer, (2023)Threshold-Based Classification to Enhance Confidence in Open Set of Legal Texts., , , , , , и . IDEAL, том 14404 из Lecture Notes in Computer Science, стр. 269-280. Springer, (2023)A Discursive Grid Approach to Model Local Coherence in Multi-document Summaries., и . SIGDIAL Conference, стр. 60-67. The Association for Computer Linguistics, (2015)UlyssesSD-Br: Stance Detection in Brazilian Political Polls., , , , , , , , , и 2 other автор(ы). EPIA, том 13566 из Lecture Notes in Computer Science, стр. 85-95. Springer, (2022)Expanding UlyssesNER-Br Named Entity Recognition Corpus with Informal User-Generated Text., , , , , , , , , и 7 other автор(ы). EPIA, том 13566 из Lecture Notes in Computer Science, стр. 767-779. Springer, (2022)A Qualitative Analysis of a Corpus of Opinion Summaries based on Aspects., , , , , , , , , и 3 other автор(ы). LAW@NAACL-HLT, стр. 62-71. The Association for Computer Linguistics, (2015)