Paulo Quaresma


ECHR: Legal Corpus for Argument Mining
Prakash Poudyal | Jaromir Savelka | Aagje Ieven | Marie Francine Moens | Teresa Goncalves | Paulo Quaresma
Proceedings of the 7th Workshop on Argument Mining

In this paper, we publicly release an annotated corpus of 42 decisions of the European Court of Human Rights (ECHR). The corpus is annotated in terms of three types of clauses useful in argument mining: premise, conclusion, and non-argument parts of the text. Furthermore, relationships among the premises and conclusions are mapped. We present baselines for three tasks that lead from unstructured texts to structured arguments. The tasks are argument clause recognition, clause relation prediction, and premise/conclusion recognition. Despite a straightforward application of the bidirectional encoders from Transformers (BERT), we obtained very promising results F1 0.765 on argument recognition, 0.511 on relation prediction, and 0.859/0.628 on premise/conclusion recognition). The results suggest the usefulness of pre-trained language models based on deep neural network architectures in argument mining. Because of the simplicity of the baselines, there is ample space for improvement in future work based on the released corpus.

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Infrastructure for the Science and Technology of Language PORTULAN CLARIN
António Branco | Amália Mendes | Paulo Quaresma | Luís Gomes | João Silva | Andrea Teixeira
Proceedings of the 1st International Workshop on Language Technology Platforms

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. It encompasses a repository, where resources and metadata are deposited for long-term archiving and access, and a workbench, where Language Technology tools and applications are made available through different modes of interaction, among many other services. It is an asset of utmost importance for the technological development of natural languages and for their preparation for the digital age, contributing to ensure the citizenship of their speakers in the information society.


Vista.ue at SemEval-2019 Task 5: Single Multilingual Hate Speech Detection Model
Kashyap Raiyani | Teresa Gonçalves | Paulo Quaresma | Vitor Nogueira
Proceedings of the 13th International Workshop on Semantic Evaluation

This paper shares insight from participating in SemEval-2019 Task 5. The main propose of this system-description paper is to facilitate the reader with replicability and to provide insightful analysis of the developed system. Here in Vista.ue, we proposed a single multilingual hate speech detection model. This model was ranked 46/70 for English Task A and 31/43 for English Task B. Vista.ue was able to rank 38/41 for Spanish Task A and 22/25 for Spanish Task B.


A Multi- versus a Single-classifier Approach for the Identification of Modality in the Portuguese Language
João Sequeira | Teresa Gonçalves | Paulo Quaresma | Amália Mendes | Iris Hendrickx
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

Fully Connected Neural Network with Advance Preprocessor to Identify Aggression over Facebook and Twitter
Kashyap Raiyani | Teresa Gonçalves | Paulo Quaresma | Vitor Beires Nogueira
Proceedings of the First Workshop on Trolling, Aggression and Cyberbullying (TRAC-2018)

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.


L2F/INESC-ID at SemEval-2017 Tasks 1 and 2: Lexical and semantic features in word and textual similarity
Pedro Fialho | Hugo Patinho Rodrigues | Luísa Coheur | Paulo Quaresma
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

This paper describes our approach to the SemEval-2017 “Semantic Textual Similarity” and “Multilingual Word Similarity” tasks. In the former, we test our approach in both English and Spanish, and use a linguistically-rich set of features. These move from lexical to semantic features. In particular, we try to take advantage of the recent Abstract Meaning Representation and SMATCH measure. Although without state of the art results, we introduce semantic structures in textual similarity and analyze their impact. Regarding word similarity, we target the English language and combine WordNet information with Word Embeddings. Without matching the best systems, our approach proved to be simple and effective.


Modality annotation for Portuguese: from manual annotation to automatic labeling
Amália Mendes | Iris Hendrickx | Liciana Ávila | Paulo Quaresma | Teresa Gonҫalves | João Sequeira
Linguistic Issues in Language Technology, Volume 14, 2016 - Modality: Logic, Semantics, Annotation, and Machine Learning

We investigate modality in Portuguese and we combine a linguistic perspective with an application-oriented perspective on modality. We design an annotation scheme reflecting theoretical linguistic concepts and apply this schema to a small corpus sample to show how the scheme deals with real world language usage. We present two schemas for Portuguese, one for spoken Brazilian Portuguese and one for written European Portuguese. Furthermore, we use the annotated data not only to study the linguistic phenomena of modality, but also to train a practical text mining tool to detect modality in text automatically. The modality tagger uses a machine learning classifier trained on automatically extracted features from a syntactic parser. As we only have a small annotated sample available, the tagger was evaluated on 11 modal verbs that are frequent in our corpus and that denote more than one modal meaning. Finally, we discuss several valuable insights into the complexity of the semantic concept of modality that derive from the process of manual annotation of the corpus and from the analysis of the results of the automatic labeling: ambiguity and the semantic and syntactic properties typically associated to one modal meaning in context, and also the interaction of modality with negation and focus. The knowledge gained from the manual annotation task leads us to propose a new unified scheme for modality that applies to the two Portuguese varieties and covers both written and spoken data.


JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information
Swarnendu Ghosh | Nibaran Das | Teresa Gonçalves | Paulo Quaresma
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014)

UM-Corpus: A Large English-Chinese Parallel Corpus for Statistical Machine Translation
Liang Tian | Derek F. Wong | Lidia S. Chao | Paulo Quaresma | Francisco Oliveira | Yi Lu | Shuo Li | Yiming Wang | Longyue Wang
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Parallel corpus is a valuable resource for cross-language information retrieval and data-driven natural language processing systems, especially for Statistical Machine Translation (SMT). However, most existing parallel corpora to Chinese are subject to in-house use, while others are domain specific and limited in size. To a certain degree, this limits the SMT research. This paper describes the acquisition of a large scale and high quality parallel corpora for English and Chinese. The corpora constructed in this paper contain about 15 million English-Chinese (E-C) parallel sentences, and more than 2 million training data and 5,000 testing sentences are made publicly available. Different from previous work, the corpus is designed to embrace eight different domains. Some of them are further categorized into different topics. The corpus will be released to the research community, which is available at the NLP2CT website.


Classifying Questions in Question Answering System Using Finite State Machines with a Simple Learning Approach
Mohammad Moinul Hoque | Teresa Goncalves | Paulo Quaresma
Proceedings of the 27th Pacific Asia Conference on Language, Information, and Computation (PACLIC 27)


Semantic Networks and Spreading Activation Process for QA improvement on text answers
José Saias | Paulo Quaresma
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology


An API for Multi-lingual Ontology Matching
Cássia Trojahn | Paulo Quaresma | Renata Vieira
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

Ontology matching consists of generating a set of correspondences between the entities of two ontologies. This process is seen as a solution to data heterogeneity in ontology-based applications, enabling the interoperability between them. However, existing matching systems are designed by assuming that the entities of both source and target ontologies are written in the same languages ( English, for instance). Multi-lingual ontology matching is an open research issue. This paper describes an API for multi-lingual matching that implements two strategies, direct translation-based and indirect. The first strategy considers direct matching between two ontologies (i.e., without intermediary ontologies), with the help of external resources, i.e., translations. The indirect alignment strategy, proposed by (Jung et al., 2009), is based on composition of alignments. We evaluate these strategies using simple string similarity based matchers and three ontologies written in English, French, and Portuguese, an extension of the OAEI benchmark test 206.


A Framework for Multilingual Ontology Mapping
Cássia Trojahn | Paulo Quaresma | Renata Vieira
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

In the field of ontology mapping, multilingual ontology mapping is an issue that is not well explored. This paper proposes a framework for mapping of multilingual Description Logics (DL) ontologies. First, the DL source ontology is translated to the target ontology language, using a lexical database or a dictionary, generating a DL translated ontology. The target and the translated ontologies are then used as input for the mapping process. The mappings are computed by specialized agents using different mapping approaches. Next, these agents use argumentation to exchange their local results, in order to agree on the obtained mappings. Based on their preferences and confidence of the arguments, the agents compute their preferred mapping sets. The arguments in such preferred sets are viewed as the set of globally acceptable arguments. A DL mapping ontology is generated as result of the mapping process. In this paper we focus on the process of generating the DL translated ontology.


Mining Linguistically Interpreted Texts
Cassiana Fagundes da Silva | Renata Vieira | Fernando Santos Osório | Paulo Quaresma
Proceedings of the 5th International Workshop on Linguistically Interpreted Corpora


An Information Retrieval System with Cooperative Behaviour
Paulo Quaresma | Irene Pimenta Rodrigues
Proceedings of the 12th Nordic Conference of Computational Linguistics (NODALIDA 1999)