Leonardo Zilio


2024

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NLP for historical Portuguese: Analysing 18th-century medical texts
Leonardo Zilio | Rafaela Radünz Lazzari | Maria Jose Bocorny Finatto
Proceedings of the 16th International Conference on Computational Processing of Portuguese

2023

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Analysing Mistranslation of Emotions in Multilingual Tweets by Online MT Tools
Hadeel Saadany | Constantin Orasan | Rocio Caro Quintana | Felix Do Carmo | Leonardo Zilio
Proceedings of the 24th Annual Conference of the European Association for Machine Translation

It is common for websites that contain User-Generated Text (UGT) to provide an automatic translation option to reach out to their linguistically diverse users. In such scenarios, the process of translating the users’ emotions is entirely automatic with no human intervention, neither for post-editing, nor for accuracy checking. In this paper, we assess whether automatic translation tools can be a successful real-life utility in transferring emotion in multilingual tweets. Our analysis shows that the mistranslation of the source tweet can lead to critical errors where the emotion is either completely lost or flipped to an opposite sentiment. We identify linguistic phenomena specific to Twitter data which pose a challenge in translation of emotions and show how frequent these features are in different language pairs. We also show that commonly-used quality metrics can lend false confidence in the performance of online MT tools specifically when the source emotion is distorted in telegraphic messages such as tweets.

2022

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PLOD: An Abbreviation Detection Dataset for Scientific Documents
Leonardo Zilio | Hadeel Saadany | Prashant Sharma | Diptesh Kanojia | Constantin Orăsan
Proceedings of the Thirteenth Language Resources and Evaluation Conference

The detection and extraction of abbreviations from unstructured texts can help to improve the performance of Natural Language Processing tasks, such as machine translation and information retrieval. However, in terms of publicly available datasets, there is not enough data for training deep-neural-networks-based models to the point of generalising well over data. This paper presents PLOD, a large-scale dataset for abbreviation detection and extraction that contains 160k+ segments automatically annotated with abbreviations and their long forms. We performed manual validation over a set of instances and a complete automatic validation for this dataset. We then used it to generate several baseline models for detecting abbreviations and long forms. The best models achieved an F1-score of 0.92 for abbreviations and 0.89 for detecting their corresponding long forms. We release this dataset along with our code and all the models publicly at https://github.com/surrey-nlp/PLOD-AbbreviationDetection

2020

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A Lexical Simplification Tool for Promoting Health Literacy
Leonardo Zilio | Liana Braga Paraguassu | Luis Antonio Leiva Hercules | Gabriel Ponomarenko | Laura Berwanger | Maria José Bocorny Finatto
Proceedings of the 1st Workshop on Tools and Resources to Empower People with REAding DIfficulties (READI)

This paper presents MedSimples, an authoring tool that combines Natural Language Processing, Corpus Linguistics and Terminology to help writers to convert health-related information into a more accessible version for people with low literacy skills. MedSimples applies parsing methods associated with lexical resources to automatically evaluate a text and present simplification suggestions that are more suitable for the target audience. Using the suggestions provided by the tool, the author can adapt the original text and make it more accessible. The focus of MedSimples lies on texts for special purposes, so that it not only deals with general vocabulary, but also with specialized terms. The tool is currently under development, but an online working prototype exists and can be tested freely. An assessment of MedSimples was carried out aiming at evaluating its current performance with some promising results, especially for informing the future developments that are planned for the tool.

2018

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Investigating Productive and Receptive Knowledge: A Profile for Second Language Learning
Leonardo Zilio | Rodrigo Wilkens | Cédrick Fairon
Proceedings of the 27th International Conference on Computational Linguistics

The literature frequently addresses the differences in receptive and productive vocabulary, but grammar is often left unacknowledged in second language acquisition studies. In this paper, we used two corpora to investigate the divergences in the behavior of pedagogically relevant grammatical structures in reception and production texts. We further improved the divergence scores observed in this investigation by setting a polarity to them that indicates whether there is overuse or underuse of a grammatical structure by language learners. This led to the compilation of a language profile that was later combined with vocabulary and readability features for classifying reception and production texts in three classes: beginner, intermediate, and advanced. The results of the automatic classification task in both production (0.872 of F-measure) and reception (0.942 of F-measure) were comparable to the current state of the art. We also attempted to automatically attribute a score to texts produced by learners, and the correlation results were encouraging, but there is still a good amount of room for improvement in this task. The developed language profile will serve as input for a system that helps language learners to activate more of their passive knowledge in writing texts.

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SW4ALL: a CEFR Classified and Aligned Corpus for Language Learning
Rodrigo Wilkens | Leonardo Zilio | Cédrick Fairon
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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An SLA Corpus Annotated with Pedagogically Relevant Grammatical Structures
Leonardo Zilio | Rodrigo Wilkens | Cédrick Fairon
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2017

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LexSubNC: A Dataset of Lexical Substitution for Nominal Compounds
Rodrigo Wilkens | Leonardo Zilio | Silvio Ricardo Cordeiro | Felipe Paula | Carlos Ramisch | Marco Idiart | Aline Villavicencio
Proceedings of the 12th International Conference on Computational Semantics (IWCS) — Short papers

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Using NLP for Enhancing Second Language Acquisition
Leonardo Zilio | Rodrigo Wilkens | Cédrick Fairon
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017

This study presents SMILLE, a system that draws on the Noticing Hypothesis and on input enhancements, addressing the lack of salience of grammatical infor mation in online documents chosen by a given user. By means of input enhancements, the system can draw the user’s attention to grammar, which could possibly lead to a higher intake per input ratio for metalinguistic information. The system receives as input an online document and submits it to a combined processing of parser and hand-written rules for detecting its grammatical structures. The input text can be freely chosen by the user, providing a more engaging experience and reflecting the user’s interests. The system can enhance a total of 107 fine-grained types of grammatical structures that are based on the CEFR. An evaluation of some of those structures resulted in an overall precision of 87%.

2016

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VerbLexPor: a lexical resource with semantic roles for Portuguese
Leonardo Zilio | Maria José Bocorny Finatto | Aline Villavicencio
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents a lexical resource developed for Portuguese. The resource contains sentences annotated with semantic roles. The sentences were extracted from two domains: Cardiology research papers and newspaper articles. Both corpora were analyzed with the PALAVRAS parser and subsequently processed with a subcategorization frames extractor, so that each sentence that contained at least one main verb was stored in a database together with its syntactic organization. The annotation was manually carried out by a linguist using an annotation interface. Both the annotated and non-annotated data were exported to an XML format, which is readily available for download. The reason behind exporting non-annotated data is that there is syntactic information collected from the parser annotation in the non-annotated data, and this could be useful for other researchers. The sentences from both corpora were annotated separately, so that it is possible to access sentences either from the Cardiology or from the newspaper corpus. The full resource presents more than seven thousand semantically annotated sentences, containing 192 different verbs and more than 15 thousand individual arguments and adjuncts.

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B2SG: a TOEFL-like Task for Portuguese
Rodrigo Wilkens | Leonardo Zilio | Eduardo Ferreira | Aline Villavicencio
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Resources such as WordNet are useful for NLP applications, but their manual construction consumes time and personnel, and frequently results in low coverage. One alternative is the automatic construction of large resources from corpora like distributional thesauri, containing semantically associated words. However, as they may contain noise, there is a strong need for automatic ways of evaluating the quality of the resulting resource. This paper introduces a gold standard that can aid in this task. The BabelNet-Based Semantic Gold Standard (B2SG) was automatically constructed based on BabelNet and partly evaluated by human judges. It consists of sets of tests that present one target word, one related word and three unrelated words. B2SG contains 2,875 validated relations: 800 for verbs and 2,075 for nouns; these relations are divided among synonymy, antonymy and hypernymy. They can be used as the basis for evaluating the accuracy of the similarity relations on distributional thesauri by comparing the proximity of the target word with the related and unrelated options and observing if the related word has the highest similarity value among them. As a case study two distributional thesauri were also developed: one using surface forms from a large (1.5 billion word) corpus and the other using lemmatized forms from a smaller (409 million word) corpus. Both distributional thesauri were then evaluated against B2SG, and the one using lemmatized forms performed slightly better.

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How Naked is the Naked Truth? A Multilingual Lexicon of Nominal Compound Compositionality
Carlos Ramisch | Silvio Cordeiro | Leonardo Zilio | Marco Idiart | Aline Villavicencio
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2015

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Distributional Thesauri for Portuguese: methodology evaluation
Rodrigo Wilkens | Leonardo Zilio | Eduardo Ferreira | Gabriel Gonçalves | Aline Villavicencio
Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology

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VerbLexPor: um recurso léxico com anotação de papéis semânticos para o português (VerbLexPor: a lexical resource annotated with semantic roles for Portuguese)
Leonardo Zilio | Maria José Bocorny Finatto | Aline Villavicencio
Proceedings of the 10th Brazilian Symposium in Information and Human Language Technology

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Post-editing a chapter of a specialized textbook into 7 languages: importance of terminological proximity with English for productivity
Ritesh Shah | Christian Boitet | Pushpak Bhattacharyya | Mithun Padmakumar | Leonardo Zilio | Ruslan Kalitvianski | Mohammad Nasiruddin | Mutsuko Tomokiyo | Sandra Castellanos Páez
Proceedings of the 12th International Conference on Natural Language Processing

2011

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Improving Lexical Alignment Using Hybrid Discriminative and Post-Processing Techniques
Paulo Schreiner | Aline Villavicencio | Leonardo Zilio | Helena M. Caseli
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology

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Automatic extraction and evaluation of MWE
Leonardo Zilio | Luiz Svoboda | Luiz Henrique Longhi Rossi | Rafael Martins Feitosa
Proceedings of the 8th Brazilian Symposium in Information and Human Language Technology