2024
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BATS-PT: Assessing Portuguese Masked Language Models in Lexico-Semantic Analogy Solving and Relation Completion
Hugo Gonçalo Oliveira
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Ricardo Rodrigues
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Bruno Ferreira
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Purificação Silvano
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Sara Carvalho
Proceedings of the 16th International Conference on Computational Processing of Portuguese - Vol. 1
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ISO 24617-8 Applied: Insights from Multilingual Discourse Relations Annotation in English, Polish, and Portuguese
Aleksandra Tomaszewska
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Purificação Silvano
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António Leal
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Evelin Amorim
Proceedings of the 20th Joint ACL - ISO Workshop on Interoperable Semantic Annotation @ LREC-COLING 2024
The main objective of this study is to contribute to multilingual discourse research by employing ISO-24617 Part 8 (Semantic Relations in Discourse, Core Annotation Schema – DR-core) for annotating discourse relations. Centering around a parallel discourse relations corpus that includes English, Polish, and European Portuguese, we initiate one of the few ISO-based comparative analyses through a multilingual corpus that aligns discourse relations across these languages. In this paper, we discuss the project’s contributions, including the annotated corpus, research findings, and statistics related to the use of discourse relations. The paper further discusses the challenges encountered in complying with the ISO standard, such as defining the scope of arguments and annotating specific relation types like Expansion. Our findings highlight the necessity for clearer definitions of certain discourse relations and more precise guidelines for argument spans, especially concerning the inclusion of connectives. Additionally, the study underscores the importance of ongoing collaborative efforts to broaden the inclusion of languages and more comprehensive datasets, with the objective of widening the reach of ISO-guided multilingual discourse research.
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MultiLexBATS: Multilingual Dataset of Lexical Semantic Relations
Dagmar Gromann
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Hugo Goncalo Oliveira
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Lucia Pitarch
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Elena-Simona Apostol
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Jordi Bernad
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Eliot Bytyçi
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Chiara Cantone
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Sara Carvalho
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Francesca Frontini
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Radovan Garabik
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Jorge Gracia
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Letizia Granata
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Fahad Khan
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Timotej Knez
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Penny Labropoulou
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Chaya Liebeskind
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Maria Pia Di Buono
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Ana Ostroški Anić
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Sigita Rackevičienė
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Ricardo Rodrigues
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Gilles Sérasset
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Linas Selmistraitis
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Mahammadou Sidibé
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Purificação Silvano
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Blerina Spahiu
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Enriketa Sogutlu
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Ranka Stanković
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Ciprian-Octavian Truică
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Giedre Valunaite Oleskeviciene
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Slavko Zitnik
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Katerina Zdravkova
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Understanding the relation between the meanings of words is an important part of comprehending natural language. Prior work has either focused on analysing lexical semantic relations in word embeddings or probing pretrained language models (PLMs), with some exceptions. Given the rarity of highly multilingual benchmarks, it is unclear to what extent PLMs capture relational knowledge and are able to transfer it across languages. To start addressing this question, we propose MultiLexBATS, a multilingual parallel dataset of lexical semantic relations adapted from BATS in 15 languages including low-resource languages, such as Bambara, Lithuanian, and Albanian. As experiment on cross-lingual transfer of relational knowledge, we test the PLMs’ ability to (1) capture analogies across languages, and (2) predict translation targets. We find considerable differences across relation types and languages with a clear preference for hypernymy and antonymy as well as romance languages.
2023
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Validation of Language Agnostic Models for Discourse Marker Detection
Mariana Damova
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Kostadin Mishev
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Giedrė Valūnaitė-Oleškevičienė
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Chaya Liebeskind
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Purificação Silvano
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Dimitar Trajanov
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Ciprian-Octavian Truica
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Elena-Simona Apostol
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Christian Chiarcos
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Anna Baczkowska
Proceedings of the 4th Conference on Language, Data and Knowledge
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ISO-DR-core Plugs into ISO-dialogue Acts for a Cross-linguistic Taxonomy of Discourse Markers
Purificação Silvano
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Mariana Damova
Proceedings of the 4th Conference on Language, Data and Knowledge
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DRIPPS: a Corpus with Discourse Relations in Perfect Participial Sentences
Purificação Silvano
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João Cordeiro
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António Leal
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Sebastião Pais
Proceedings of the 4th Conference on Language, Data and Knowledge
2022
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ISO-based Annotated Multilingual Parallel Corpus for Discourse Markers
Purificação Silvano
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Mariana Damova
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Giedrė Valūnaitė Oleškevičienė
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Chaya Liebeskind
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Christian Chiarcos
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Dimitar Trajanov
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Ciprian-Octavian Truică
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Elena-Simona Apostol
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Anna Baczkowska
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Discourse markers carry information about the discourse structure and organization, and also signal local dependencies or epistemological stance of speaker. They provide instructions on how to interpret the discourse, and their study is paramount to understand the mechanism underlying discourse organization. This paper presents a new language resource, an ISO-based annotated multilingual parallel corpus for discourse markers. The corpus comprises nine languages, Bulgarian, Lithuanian, German, European Portuguese, Hebrew, Romanian, Polish, and Macedonian, with English as a pivot language. In order to represent the meaning of the discourse markers, we propose an annotation scheme of discourse relations from ISO 24617-8 with a plug-in to ISO 24617-2 for communicative functions. We describe an experiment in which we applied the annotation scheme to assess its validity. The results reveal that, although some extensions are required to cover all the multilingual data, it provides a proper representation of discourse markers value. Additionally, we report some relevant contrastive phenomena concerning discourse markers interpretation and role in discourse. This first step will allow us to develop deep learning methods to identify and extract discourse relations and communicative functions, and to represent that information as Linguistic Linked Open Data (LLOD).
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The place of ISO-Space in Text2Story multilayer annotation scheme
António Leal
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Purificação Silvano
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Evelin Amorim
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Inês Cantante
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Fátima Silva
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Alípio Mario Jorge
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Ricardo Campos
Proceedings of the 18th Joint ACL - ISO Workshop on Interoperable Semantic Annotation within LREC2022
Reasoning about spatial information is fundamental in natural language to fully understand relationships between entities and/or between events. However, the complexity underlying such reasoning makes it hard to represent formally spatial information. Despite the growing interest on this topic, and the development of some frameworks, many problems persist regarding, for instance, the coverage of a wide variety of linguistic constructions and of languages. In this paper, we present a proposal of integrating ISO-Space into a ISO-based multilayer annotation scheme, designed to annotate news in European Portuguese. This scheme already enables annotation at three levels, temporal, referential and thematic, by combining postulates from ISO 24617-1, 4 and 9. Since the corpus comprises news articles, and spatial information is relevant within this kind of texts, a more detailed account of space was required. The main objective of this paper is to discuss the process of integrating ISO-Space with the existing layers of our annotation scheme, assessing the compatibility of the aforementioned parts of ISO 24617, and the problems posed by the harmonization of the four layers and by some specifications of ISO-Space.
2021
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Developing a multilayer semantic annotation scheme based on ISO standards for the visualization of a newswire corpus
Purificação Silvano
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António Leal
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Fátima Silva
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Inês Cantante
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Fatima Oliveira
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Alípio Mario Jorge
Proceedings of the 17th Joint ACL - ISO Workshop on Interoperable Semantic Annotation
In this paper, we describe the process of developing a multilayer semantic annotation scheme designed for extracting information from a European Portuguese corpus of news articles, at three levels, temporal, referential and semantic role labelling. The novelty of this scheme is the harmonization of parts 1, 4 and 9 of the ISO 24617 Language resource management - Semantic annotation framework. This annotation framework includes a set of entity structures (participants, events, times) and a set of links (temporal, aspectual, subordination, objectal and semantic roles) with several tags and attribute values that ensure adequate semantic and visual representations of news stories.