Bootstrapping a Portuguese WordNet from Galician, Spanish and English wordnets

Series: Lecture notes in computer science, ISSN 0302-9743, vol. 8854In this article we exploit the possibility on bootstrapping an European Portuguese WordNet from the English, Spanish and Galician wordnets using Probabilistic Translation Dictionaries automatically created from parallel corpora. The process generated a total of 56~770 synsets and 97~058 variants. An evaluation of the results using the Brazilian OpenWordNet-PT as a gold standard resulted on a precision varying from 53\% to 75\% percent, depending on the cut-line. The results were satisfying and comparable to similar experiments using the WN-Toolkit.PEst-OE/EEI/UI0752/2014, TIN2012-38584-C06-01, TIN2012-38584-C06-0

Acquiring Domain-Specific Knowledge for WordNet from a Terminological Database

In this research we explore a terminological database (Termoteca) in order to expand the Portuguese and Galician wordnets (PULO and Galnet) with the addition of new synset variants (word forms for a concept), usage examples for the variants, and synset glosses or definitions. The methodology applied in this experiment is based on the alignment between concepts of WordNet (synsets) and concepts described in Termoteca (terminological records), taking into account the lexical forms in both resources, their morphological category and their knowledge domains, using the information provided by the WordNet Domains Hierarchy and the Termoteca field domains to reduce the incidence of polysemy and homography in the results of the experiment. The results obtained confirm our hypothesis that the combined use of the semantic domain information included in both resources makes it possible to minimise the problem of lexical ambiguity and to obtain a very acceptable index of precision in terminological information extraction tasks, attaining a precision above 89% when there are two or more different languages sharing at least one lexical form between the synset in Galnet and the Termoteca record

Extending the Galician Wordnet Using a Multilingual Bible Through Lexical Alignment and Semantic Annotation

In this paper we describe the methodology and evaluation of the expansion of Galnet - the Galician wordnet - using a multilingual Bible through lexical alignment and semantic annotation. For this experiment we used the Galician, Portuguese, Spanish, Catalan and English versions of the Bible. They were annotated with part-of-speech and WordNet sense using FreeLing. The resulting synsets were aligned, and new variants for the Galician language were extracted. After manual evaluation the approach presented a 96.8% accuracy

Experiments on enlarging a lexical ontology

This paper presents two simple experiments performed in order to enlarge the coverage of PULO, a Lexical Ontology, based and aligned with the Princeton WordNet. The first experiment explores the triangulation of the Galician, Catalan and Castillian wordnets, with translation dictionaries from the Apertium project. The second, explores Dicionário-Aberto entries, in order to extract synsets from its definitions. Although similar approaches were already applied for different languages, this document aims at documenting their results for the PULO case

As Wordnets do Português

Series: "Oslo Studies in Language". ISSN 1890-9639. 7(1), 2015.Not many years ago it was usual to comment on the lack of an open lexical- semantic knowledge base, following the lines of Princeton WordNet, but for Portuguese. Today, the landscape has changed significantly, and re- searchers that need access to this specific kind of resource have not one, but several alternatives to choose from. The present article describes the wordnet-like resources currently available for Portuguese. It provides some context on their origin, creation approach, size and license for utilization. Apart from being an obvious starting point for those looking for a computational resource with information on the meaning of Portuguese words, this article describes the resources available, compares them and lists some plans for future work, sketching ideas for potential collaboration between the projects described.CLUPFundação para a Ciência e a Tecnologia (FCT

Let's play with proverbs? NLP tools and resources for iCALL applications around proverbs for PFL

Proverbs are an important form of cultural expression of a society and are related to various areas of knowledge and human experience (González Rey, 2002). While linguistic elements in widespread use, proverbs are very rich structures both from a cultural and from a linguistic point of view and can therefore contribute significantly to the teaching of languages, both native and foreign (Council of Europe, 2001). However, though there are extensive collections of Portuguese proverbs with tens of thousands of forms and its variants (Reis, in preparation), its automatic identification in texts is quite difficult, given its formal variation, both lexical and syntactic (Chacoto, 1994). Nevertheless, using real examples, where proverbs are used in a natural or spontaneous discourse context, is a more natural way to learn and teach the complex conditions and communicative situations that determine the use and meaning of these expressions. On the other hand, frequency indices associated with proverbs and its variants would allow one to select the most common expressions. These are precisely the most interesting forms from the point of view of their teaching/learning and could serve as a basis for the construction of educational games, particularly for learning Portuguese autonomously as a foreign language (PFL) assisted by computer. To make this possible, it is necessary, first of all, be able to recognize the occurrence of proverbs in the texts (Rassi et al. 2014), including the instances where these expressions are presented in a truncated or creatively modified form, for example, to better suit the communicative situation or to produce new and more expressive meanings. In this paper, we present an on-going project, which aims at automatic identification of proverbs in texts. In this interdisciplinary study, we combine natural language processing tools with questionnaires construction techniques for teaching purposes (Hoshino and Nakagawa 2005, Correia et al. 2010). This is illustrated here with different sets of formats that can be built based on the knowledge of the form and variation of proverbs, as well as their frequency in corpora.info:eu-repo/semantics/publishedVersio

Assessing Lexical-Semantic Regularities in Portuguese Word Embeddings

Models of word embeddings are often assessed when solving syntactic and semantic analogies. Among the latter, we are interested in relations that one would find in lexical-semantic knowledge bases like WordNet, also covered by some analogy test sets for English. Briefly, this paper aims to study how well pretrained Portuguese word embeddings capture such relations. For this purpose, we created a new test, dubbed TALES, with an exclusive focus on Portuguese lexical-semantic relations, acquired from lexical resources. With TALES, we analyse the performance of methods previously used for solving analogies, on different models of Portuguese word embeddings. Accuracies were clearly below the state of the art in analogies of other kinds, which shows that TALES is a challenging test, mainly due to the nature of lexical-semantic relations, i.e., there are many instances sharing the same argument, thus allowing for several correct answers, sometimes too many to be all included in the dataset. We further inspect the results of the best performing combination of method and model to find that some acceptable answers had been considered incorrect. This was mainly due to the lack of coverage by the source lexical resources and suggests that word embeddings may be a useful source of information for enriching those resources, something we also discuss

ASAPP 2.0: Advancing the state-of-the-art of semantic textual similarity for Portuguese

Semantic Textual Similarity (STS) aims at computing the proximity of meaning transmitted by two sentences. In 2016, the ASSIN shared task targeted STS in Portuguese and released training and test collections. This paper describes the development of ASAPP, a system that participated in ASSIN, but has been improved since then, and now achieves the best results in this task. ASAPP learns a STS function from a broad range of lexical, syntactic, semantic and distributional features. This paper describes the features used in the current version of ASAPP, and how they are exploited in a regression algorithm to achieve the best published results for ASSIN to date, in both European and Brazilian Portuguese

Multilingual sentiment analysis in social media.

252 p.This thesis addresses the task of analysing sentiment in messages coming from social media. The ultimate goal was to develop a Sentiment Analysis system for Basque. However, because of the socio-linguistic reality of the Basque language a tool providing only analysis for Basque would not be enough for a real world application. Thus, we set out to develop a multilingual system, including Basque, English, French and Spanish.The thesis addresses the following challenges to build such a system:- Analysing methods for creating Sentiment lexicons, suitable for less resourced languages.- Analysis of social media (specifically Twitter): Tweets pose several challenges in order to understand and extract opinions from such messages. Language identification and microtext normalization are addressed.- Research the state of the art in polarity classification, and develop a supervised classifier that is tested against well known social media benchmarks.- Develop a social media monitor capable of analysing sentiment with respect to specific events, products or organizations