no code implementations • COLING (ArgMining) 2020 • Prakash Poudyal, Jaromir Savelka, Aagje Ieven, Marie Francine Moens, Teresa Goncalves, Paulo Quaresma
The corpus is annotated in terms of three types of clauses useful in argument mining: premise, conclusion, and non-argument parts of the text.
no code implementations • LILT 2016 • Amália Mendes, Iris Hendrickx, Liciana Ávila, Paulo Quaresma, Teresa Gonҫalves, João Sequeira
We investigate modality in Portuguese and we combine a linguistic perspective with an application-oriented perspective on modality.
no code implementations • 23 Apr 2021 • Bodhisatwa Mandal, Swarnendu Ghosh, Teresa Gonçalves, Paulo Quaresma, Mita Nasipuri, Nibaran Das
Convolutional neural networks often generate multiple logits and use simple techniques like addition or averaging for loss computation.
no code implementations • LREC 2020 • Ant{\'o}nio Branco, Am{\'a}lia Mendes, Paulo Quaresma, Lu{\'\i}s Gomes, Jo{\~a}o Silva, Andrea Teixeira
This paper presents the PORTULAN CLARIN Research Infrastructure for the Science and Technology of Language, which is part of the European research infrastructure CLARIN ERIC as its Portuguese national node, and belongs to the Portuguese National Roadmap of Research Infrastructures of Strategic Relevance.
no code implementations • 3 Sep 2019 • Paulo Quaresma, Vitor Beires Nogueira, Kashyap Raiyani, Roy Bayot, Teresa Gonçalves
Automatic reasoning about textual information is a challenging task in modern Natural Language Processing (NLP) systems.
no code implementations • SEMEVAL 2019 • Kashyap Raiyani, Teresa Gon{\c{c}}alves, Paulo Quaresma, Vitor Nogueira
This paper shares insight from participating in SemEval-2019 Task 5.
no code implementations • COLING 2018 • Kashyap Raiyani, Teresa Gon{\c{c}}alves, Paulo Quaresma, Vitor Beires Nogueira
Paper presents the different methodologies developed {\&} tested and discusses their results, with the goal of identifying the best possible method for the aggression identification problem in social media.
no code implementations • SEMEVAL 2017 • Pedro Fialho, Hugo Patinho Rodrigues, Lu{\'\i}sa Coheur, Paulo Quaresma
This paper describes our approach to the SemEval-2017 {``}Semantic Textual Similarity{''} and {``}Multilingual Word Similarity{''} tasks.
Abstract Meaning Representation
Semantic Textual Similarity
+2
no code implementations • LREC 2014 • Liang Tian, Derek F. Wong, Lidia S. Chao, Paulo Quaresma, Francisco Oliveira, Yi Lu, Shuo Li, Yiming Wang, Long-Yue Wang
This paper describes the acquisition of a large scale and high quality parallel corpora for English and Chinese.