Gil Rocha

Gil Rocha

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26
Publications
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170
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Publications

Publications (26)
Article
Full-text available
Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are st...
Preprint
Full-text available
Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are st...
Conference Paper
Interest in argument mining has resulted in an increasing number of argument annotated corpora. However, most focus on English texts with explicit argumentative discourse markers, such as persuasive essays or legal documents. Conversely, we report on the first extensive and consolidated Portuguese argument annotation project focused on opinion arti...
Chapter
Annotating a corpus with argument structures is a complex task, and it is even more challenging when addressing text genres where argumentative discourse markers do not abound. We explore a corpus of opinion articles annotated by multiple annotators, providing diverse perspectives of the argumentative content therein. New annotation aggregation met...
Article
Full-text available
The Natural Language Processing (NLP) community has witnessed huge improvements in the last years. However, most achievements are evaluated on benchmarked curated corpora, with little attention devoted to user-generated content and less-resourced languages. Despite the fact that recent approaches target the development of multi-lingual tools and mo...
Chapter
Unsupervised language adaptation aims to improve the cross-lingual ability of models that are fine-tuned on a specific task and source language, without requiring labeled data on the target language. On the other hand, recent multilingual language models (such as mBERT) have achieved new state-of-the-art results on a variety of tasks and languages,...
Chapter
While Argument Mining has seen increasing success in monolingual settings, especially for the English language, other less-resourced languages are still lagging behind. In this paper, we build a Portuguese projected version of the Persuasive Essays corpus and evaluate it both intrinsically (through back-projection) and extrinsically (in a sequence...
Chapter
Recent advances in pre-trained language models revolutionized the field of natural language processing. However, these approaches require large-scale annotated resources, that are only available for some languages. Collecting data in every language is unrealistic, hence the growing interest in cross-lingual methods that can leverage the knowledge a...
Article
Full-text available
The task of coreference resolution has attracted considerable attention in the literature due to its importance in deep language understanding and its potential as a subtask in a variety of complex natural language processing problems. In this study, we outlined the field’s terminology, describe existing metrics, their differences and shortcomings,...
Chapter
In recent years, public institutions have undergone a progressive modernization process, bringing several administrative services to be provided electronically. Some institutions are responsible for analyzing citizen complaints, which come in huge numbers and are mainly provided in free-form text, demanding for some automatic way to process them, a...
Preprint
In this paper, we describe DeFactoNLP, the system we designed for the FEVER 2018 Shared Task. The aim of this task was to conceive a system that can not only automatically assess the veracity of a claim but also retrieve evidence supporting this assessment from Wikipedia. In our approach, the Wikipedia documents whose Term Frequency-Inverse Documen...
Article
Full-text available
Recognizing textual entailment comprises the task of determining semantic entailment relations between text fragments. A text fragment entails another text fragment if, from the meaning of the former, one can infer the meaning of the latter. If such relation is bidirectional, then we are in the presence of a paraphrase. Automatically recognizing te...
Conference Paper
Full-text available
Argumentation mining aims to detect and identify the argumentative content expressed in text. In this paper we present a relation-based approach that aims to capture the relation of inference between the premise and conclusion. We follow a supervised machine learning approach and explore features at different levels of abstraction. Then, we apply t...
Conference Paper
The aim of textual entailment and paraphrase recognition is to determine whether the meaning of a text fragment can be inferred (is entailed) from the meaning of another text fragment. In this paper, we address the task of automatically recognizing textual entailment (RTE) and paraphrases from text written in the Portuguese language employing super...
Conference Paper
Full-text available
The aim of coreference resolution is to automatically determine all linguistic expressions included in a piece of text that refer to the same entity. Following the mention-pair model, we employ machine learning techniques to address coreference resolution from text written in Portuguese. Based on a modest annotated corpus, we highlight the impact t...
Conference Paper
Full-text available
The aim of argumentation mining is the automatic detection and identification of the argumentative structure contained within a piece of natural language text. In this paper we present the ArgMine Framework: an alignment of tools and processes that facilitate and partially automate argumentation mining research. We also report on a preliminary expl...

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