15 research outputs found

    A survey on author profiling, deception, and irony detection for the Arabic language

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    "This is the peer reviewed version of the following article: [FULL CITE], which has been published in final form at [Link to final article using the DOI]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[EN] The possibility of knowing people traits on the basis of what they write is a field of growing interest named author profiling. To infer a user's gender, age, native language, language variety, or even when the user lies, simply by analyzing her texts, opens a wide range of possibilities from the point of view of security. In this paper, we review the state of the art about some of the main author profiling problems, as well as deception and irony detection, especially focusing on the Arabic language.Qatar National Research Fund, Grant/Award Number: NPRP 9-175-1-033Rosso, P.; Rangel-Pardo, FM.; Hernandez-Farias, DI.; Cagnina, L.; Zaghouani, W.; Charfi, A. (2018). A survey on author profiling, deception, and irony detection for the Arabic language. Language and Linguistics Compass. 12(4):1-20. https://doi.org/10.1111/lnc3.12275S120124Abuhakema , G. Faraj , R. Feldman , A. Fitzpatrick , E. 2008 Annotating an arabic learner corpus for error Proceedings of The sixth international conference on Language Resources and Evaluation, LREC 2008Adouane , W. Dobnik , S. 2017 Identification of languages in algerian arabic multilingual documents Proceedings of The Third Arabic Natural Language Processing Workshop (WANLP)Adouane , W. Semmar , N. Johansson , R 2016a Romanized berber and romanized arabic automatic language identification using machine learning Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects; COLING 53 61Adouane , W. Semmar , N. Johansson , R. 2016b ASIREM participation at the discriminating similar languages shared task 2016 Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects; COLING 163 169Adouane , W. Semmar , N. Johansson , R. Bobicev , V. 2016c Automatic detection of arabicized berber and arabic varieties Proceedings of the Third Workshop on NLP for Similar Languages, Varieties and Dialects; COLING 63 72Alfaifi , A. Atwell , E. Hedaya , I. 2014 Arabic learner corpus (ALC) v2: A new written and spoken corpus of Arabic learnersAlharbi , K. 2015 The irony volcano explodes black comedyAli , A. Bell , P. Renals , S. 2015 Automatic dialect detection in Arabic broadcast speechAlmeman , K. Lee , M. 2013 Automatic building of Arabic multi dialect text corpora by bootstrapping dialect words 1 6Aloshban , N. Al-Dossari , H. 2016 A new approach for group spam detection in social media for Arabic language (AGSD) 20 23Al-Sabbagh , R. Girju , R. 2012 YADAC: Yet another dialectal Arabic corpusAlsmearat , K. Al-Ayyoub , M. Al-Shalabi , R. 2014 An extensive study of the bag-of-words approach for gender identification of Arabic articlesAlsmearat , K. Shehab , M. Al-Ayyoub , M. Al-Shalabi , R. Kanaan , G. 2015 Emotion analysis of Arabic articles and its impact on identifying the authors genderArfath , P. Al-Badrashiny , M. Diab , M. El Kholy , A. Eskander , R. Habash , N. Pooleery , M. Rambow , O. Roth , R. M. 2014 MADAMIRA: A fast, comprehensive tool for morphological analysis and disambiguation of ArabicBarbieri , F. Basile , V. Croce , D. Nissim , M. Novielli , N. Patti , V. 2016 Overview of the Evalita 2016 sentiment polarity classification taskBarbieri , F. Saggion , H 2014 Modelling irony in twitter 56 64Barbieri , F. Saggion , H. Ronzano , F 2014 Modelling sarcasm in Twitter, a novel approachBasile , V. Bolioli , A. Nissim , M. Patti , V. Rosso , P. 2014 Overview of the Evalita 2014 sentiment polarity classification taskBlanchard, D., Tetreault, J., Higgins, D., Cahill, A., & Chodorow, M. (2013). TOEFL11: A CORPUS OF NON-NATIVE ENGLISH. ETS Research Report Series, 2013(2), i-15. doi:10.1002/j.2333-8504.2013.tb02331.xBosco, C., Patti, V., & Bolioli, A. (2013). Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT. IEEE Intelligent Systems, 28(2), 55-63. doi:10.1109/mis.2013.28Bouamor , H. Habash , N. Salameh , M. Zaghouani , W. Rambow , O. Abdulrahim , D. Oflazer , K. 2018 The MADAR Arabic Dialect Corpus and LexiconBouchlaghem , R. Elkhlifi , A. Faiz , R. 2014 Tunisian dialect Wordnet creation and enrichment using web resources and other Wordnets 104 113 https://doi.org/10.3115/v1/W14-3613Boujelbane , R. BenAyed , S. Belguith , L. H. 2013 Building bilingual lexicon to create dialect Tunisian corpora and adapt language modelCagnina L. Rosso , P 2015 Classification of deceptive opinions using a low dimensionality representationCavalli-Sforza , V. Saddiki , H. Bouzoubaa , K. Abouenour , L. Maamouri , M. Goshey , E. 2013 Bootstrapping a Wordnet for an Arabic dialect from other Wordnets and dictionary resourcesCotterell , R. Callison-Burch , C. 2014 A multi-dialect, multi-genre corpus of informal written ArabicDahlmeier , D. Tou Ng , H. Mei Wu , S. 2013 Building a large annotated corpus of learner English: the NUS corpus of learner English 22 31Darwish , K. Sajjad , H. Mubarak , H. 2014 Verifiably effective Arabic dialect identification 1465 1468Duh , K. Kirchhoff , K. 2006 Lexicon acquisition for dialectal Arabic using transductive learningElfardy , E. Diab , M. T. 2013 Sentence level dialect identification in Arabic 456 461Estival , D. Gaustad , T. Hutchinson , B. Bao-Pham , S. Radford , W. 2008 Author profiling for English and Arabic emailsFitzpatrick, E., Bachenko, J., & Fornaciari, T. (2015). Automatic Detection of Verbal Deception. Synthesis Lectures on Human Language Technologies, 8(3), 1-119. doi:10.2200/s00656ed1v01y201507hlt029Franco-Salvador, M., Rangel, F., Rosso, P., Taulé, M., & Antònia Martít, M. (2015). Language Variety Identification Using Distributed Representations of Words and Documents. Experimental IR Meets Multilinguality, Multimodality, and Interaction, 28-40. doi:10.1007/978-3-319-24027-5_3Ghosh , A. Li , G. Veale , T. Rosso , P. Shutova , E. Barnden , J. Reyes , A. 2015 Semeval-2015 task 11: Sentiment analysis of figurative language in twitter 470 478Graff , D. Maamouri , M. 2012 Developing LMF-XML bilingual dictionaries for colloquial Arabic dialects 269 274Habash , N. Khalifa , S. Eryani , F. Rambow , O. Abdulrahim , D. Erdmann , A. Saddiki , H. 2018 Unified Guidelines and Resources for Arabic Dialect OrthographyHabash , N. Rambow , O. Kiraz , G. 2005 Morphological analysis and generation for Arabic dialectsHaggan, M. (1991). Spelling errors in native Arabic-speaking English majors: A comparison between remedial students and fourth year students. System, 19(1-2), 45-61. doi:10.1016/0346-251x(91)90007-cHassan , H. Daud , N. M. 2011 Corpus analysis of conjunctions: Arabic learners difficulties with collocationsHayes-Harb, R. (2006). Native Speakers of Arabic and ESL Texts: Evidence for the Transfer of Written Word Identification Processes. TESOL Quarterly, 40(2), 321. doi:10.2307/40264525Hernández-Farías, I., Benedí, J.-M., & Rosso, P. (2015). Applying Basic Features from Sentiment Analysis for Automatic Irony Detection. Lecture Notes in Computer Science, 337-344. doi:10.1007/978-3-319-19390-8_38Hernández Fusilier, D., Montes-y-Gómez, M., Rosso, P., & Guzmán Cabrera, R. (2015). Detecting positive and negative deceptive opinions using PU-learning. Information Processing & Management, 51(4), 433-443. doi:10.1016/j.ipm.2014.11.001Karoui , J. Benamara , F. Moriceau , V. Aussenac-Gilles , N. Hadrich Belguith , L. 2015 Towards a contextual pragmatic model to detect irony in tweetsKaroui , J. Zitoune , F. B. Moriceau , V. 2017 SOUKHRIA: Towards an irony detection system for Arabic in social mediaLjubesic , N. Mikelic , N. Boras , D. 2007 Language identification: How to distinguish similar languagesLópez-Monroy, A. P., Montes-y-Gómez, M., Escalante, H. J., Villaseñor-Pineda, L., & Stamatatos, E. (2015). Discriminative subprofile-specific representations for author profiling in social media. Knowledge-Based Systems, 89, 134-147. doi:10.1016/j.knosys.2015.06.024Magdy, W., Darwish, K., & Weber, I. (2016). #FailedRevolutions: Using Twitter to study the antecedents of ISIS support. First Monday. doi:10.5210/fm.v21i2.6372Maier , W. Gomez-Rodriguez , C. 2014 Language variety identification in Spanish tweetsMalmasi , S. Dras , M. 2014 Arabic native language identificationMechti , S. Abbassi , A. Belguith , L. H. Faiz , R. 2016 An empirical method using features combination for Arabic native language identificationMukherjee, A., Liu, B., & Glance, N. (2012). Spotting fake reviewer groups in consumer reviews. Proceedings of the 21st international conference on World Wide Web - WWW ’12. doi:10.1145/2187836.2187863Proceedings of the EMNLP’2014 Workshop on Language Technology for Closely Related Languages and Language Variants. (2014). doi:10.3115/v1/w14-42Pennebaker , J. W. Chung , C. K. Ireland , M. E. Gonzales , A. L. Booth , R. J. 2007 The development and psychometric properties of LIWC2007 http://www.liwc.net/LIWC2007LanguageManual.pdf http://liwc.netPotthast , M. Rangel , F. Tschuggnall , M. Stamatatos , E. Rosso , P. Stein , B. 2017 Overview of PAN'17 G. Jones 10456 Springer, ChamRandall M. Groom , N. 2009 The BUiD Arab learner corpus: a resource for studying the acquisition of l2 English spellingRangel , F. Rosso , P. 2015 On the multilingual and genre robustness of emographs for author profiling in social media 274 280 Springer-Verlag, LNCSRangel, F., & Rosso, P. (2016). On the impact of emotions on author profiling. Information Processing & Management, 52(1), 73-92. doi:10.1016/j.ipm.2015.06.003Rangel , F. Rosso , P. Koppel , M. Stamatatos , E. Inches , G. 2013 Overview of the author profiling task at PAN 2013 P. Forner R. Navigli D. TufisRangel , F. Rosso , P. Potthast , M. Stein , B. Daelemans , W. 2015 Overview of the 3rd author profiling task at PAN 2015 L. Cappellato N. Ferro G. Jones E. San JuanRangel , F. Rosso , P. Verhoeven , B. Daelemans , W. Potthast , M. Stein , B. 2016 Overview of the 4th author profiling task at PAN 2016: Cross-genre evaluationsRefaee , E. Rieser , V. 2014 An Arabic twitter corpus for subjectivity and sentiment analysis 2268 2273Reyes, A., Rosso, P., & Buscaldi, D. (2012). From humor recognition to irony detection: The figurative language of social media. Data & Knowledge Engineering, 74, 1-12. doi:10.1016/j.datak.2012.02.005Reyes, A., Rosso, P., & Veale, T. (2012). A multidimensional approach for detecting irony in Twitter. Language Resources and Evaluation, 47(1), 239-268. doi:10.1007/s10579-012-9196-xRosso, P., & Cagnina, L. C. (2017). Deception Detection and Opinion Spam. Socio-Affective Computing, 155-171. doi:10.1007/978-3-319-55394-8_8Saâdane , H. 2015 Traitement Automatique de L'Arabe Dialectalise: Aspects Methodologiques et AlgorithmiquesSaâdane , H. Nouvel , D. Seffih , H. Fluhr , C. 2017 Une approche linguistique pour la détection des dialectes arabesSadat , F. Kazemi , F. Farzindar , A. 2014 Automatic identification of Arabic language varieties and dialects in social mediaSadhwani , P. 2005 Phonological and orthographic knowledge: An Arab-Emirati perspectiveSchler , J. Koppel , M. Argamon , S. Pennebaker , J. W. 2006 Effects of age and gender on blogging 199 205Shoufan , A. Al-Ameri , S. 2015 Natural language processing for dialectical Arabic: A surveySoliman , T. Elmasry , M. Hedar , A-R. Doss , M. 2013 MINING SOCIAL NETWORKS' ARABIC SLANG COMMENTSSulis, E., Irazú Hernández Farías, D., Rosso, P., Patti, V., & Ruffo, G. (2016). Figurative messages and affect in Twitter: Differences between #irony, #sarcasm and #not. Knowledge-Based Systems, 108, 132-143. doi:10.1016/j.knosys.2016.05.035Tetreault , J. Blanchard , D. Cahill , A. 2013 A report on the first native language identification shared task Proceedings of the 8th Workshop on Innovative Use of NLP for Building Educational Applications 48 57Tillmann , C. Mansour , S. Al Onaizan , Y. 2014 Improved sentence-level Arabic dialect classification Proceedings of the VarDia006C Workshop 110 119Tono, Y. (2012). International Corpus of Crosslinguistic Interlanguage: Project overview and a case study on the acquisition of new verb co-occurrence patterns. Tokyo University of Foreign Studies, 27-46. doi:10.1075/tufs.4.07tonWahsheh , H. A. Al-Kabi , M. N. Alsmadi , I. M. 2013b SPAR: A system to detect spam in Arabic opinionsZaghouani , W. Charfi , A. 2018a Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identification Miyazaki, JapanZaghouani , W. Charfi , A. 2018b Guidelines and Annotation Framework for Arabic Author Profiling Miyazaki, JapanZaghouani , W. Mohit , B. Habash , N. Obeid , O. Tomeh , N. Rozovskaya , A. Farra , N. Alkuhlani , S. Oflazer , K. 2014 Large scale Arabic error annotation: Guidelines and frameworkZaghouani , W. Habash , N. Bouamor , H. Rozovskaya , A. Mohit , B. Heider , A. Oflazer , K. 2015 Correction annotation for non-native Arabic texts: Guidelines and corpus Proceedings of the Association for Computational Linguistics, Fourth Linguistic Annotation Workshop 129 139Zaidan , O. F. Callison-Burch , C 2011 The Arabic online commentary dataset: An annotated dataset of informal Arabic with high dialectal content Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers -Volume 2 Association for Computational Linguistics 37 41Zaidan, O. F., & Callison-Burch, C. (2014). Arabic Dialect Identification. Computational Linguistics, 40(1), 171-202. doi:10.1162/coli_a_00169Zampieri , M. Gebre , B. G. 2012 Automatic identification of language varieties: The case of PortugueseZampieri , M. Tan , L. Ljubesic , N. Tiedemann , J. 2014 A report on the DSL shared task 2014 Proceedings of the First Workshop on Applying NLP Tools to Similar Languages, Varieties and Dialects 58 67Zampieri , M. Tan , L. Ljubesic , N. Tiedemann , J. Nakov , P. 2015 Overview of the DSL shared task 2015 1Zbib , R. Malchiodi , E. Devlin , J. Stallard , D. Matsoukas , S. Schwartz , R. Makhoul , J. Zaidan , O. F. Callison Burch , C. 2012 Machine translation of Arabic dialects Proceedings of the 2012 conference of the North American chapter of the Association for Computational Linguistics: Human language technologies Association for Computational Linguistics 49 5

    A Computational Lexicon and Representational Model for Arabic Multiword Expressions

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    The phenomenon of multiword expressions (MWEs) is increasingly recognised as a serious and challenging issue that has attracted the attention of researchers in various language-related disciplines. Research in these many areas has emphasised the primary role of MWEs in the process of analysing and understanding language, particularly in the computational treatment of natural languages. Ignoring MWE knowledge in any NLP system reduces the possibility of achieving high precision outputs. However, despite the enormous wealth of MWE research and language resources available for English and some other languages, research on Arabic MWEs (AMWEs) still faces multiple challenges, particularly in key computational tasks such as extraction, identification, evaluation, language resource building, and lexical representations. This research aims to remedy this deficiency by extending knowledge of AMWEs and making noteworthy contributions to the existing literature in three related research areas on the way towards building a computational lexicon of AMWEs. First, this study develops a general understanding of AMWEs by establishing a detailed conceptual framework that includes a description of an adopted AMWE concept and its distinctive properties at multiple linguistic levels. Second, in the use of AMWE extraction and discovery tasks, the study employs a hybrid approach that combines knowledge-based and data-driven computational methods for discovering multiple types of AMWEs. Third, this thesis presents a representative system for AMWEs which consists of multilayer encoding of extensive linguistic descriptions. This project also paves the way for further in-depth AMWE-aware studies in NLP and linguistics to gain new insights into this complicated phenomenon in standard Arabic. The implications of this research are related to the vital role of the AMWE lexicon, as a new lexical resource, in the improvement of various ANLP tasks and the potential opportunities this lexicon provides for linguists to analyse and explore AMWE phenomena

    Language technologies for a multilingual Europe

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    This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)

    Wiktionary: The Metalexicographic and the Natural Language Processing Perspective

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    Dictionaries are the main reference works for our understanding of language. They are used by humans and likewise by computational methods. So far, the compilation of dictionaries has almost exclusively been the profession of expert lexicographers. The ease of collaboration on the Web and the rising initiatives of collecting open-licensed knowledge, such as in Wikipedia, caused a new type of dictionary that is voluntarily created by large communities of Web users. This collaborative construction approach presents a new paradigm for lexicography that poses new research questions to dictionary research on the one hand and provides a very valuable knowledge source for natural language processing applications on the other hand. The subject of our research is Wiktionary, which is currently the largest collaboratively constructed dictionary project. In the first part of this thesis, we study Wiktionary from the metalexicographic perspective. Metalexicography is the scientific study of lexicography including the analysis and criticism of dictionaries and lexicographic processes. To this end, we discuss three contributions related to this area of research: (i) We first provide a detailed analysis of Wiktionary and its various language editions and dictionary structures. (ii) We then analyze the collaborative construction process of Wiktionary. Our results show that the traditional phases of the lexicographic process do not apply well to Wiktionary, which is why we propose a novel process description that is based on the frequent and continual revision and discussion of the dictionary articles and the lexicographic instructions. (iii) We perform a large-scale quantitative comparison of Wiktionary and a number of other dictionaries regarding the covered languages, lexical entries, word senses, pragmatic labels, lexical relations, and translations. We conclude the metalexicographic perspective by finding that the collaborative Wiktionary is not an appropriate replacement for expert-built dictionaries due to its inconsistencies, quality flaws, one-fits-all-approach, and strong dependence on expert-built dictionaries. However, Wiktionary's rapid and continual growth, its high coverage of languages, newly coined words, domain-specific vocabulary and non-standard language varieties, as well as the kind of evidence based on the authors' intuition provide promising opportunities for both lexicography and natural language processing. In particular, we find that Wiktionary and expert-built wordnets and thesauri contain largely complementary entries. In the second part of the thesis, we study Wiktionary from the natural language processing perspective with the aim of making available its linguistic knowledge for computational applications. Such applications require vast amounts of structured data with high quality. Expert-built resources have been found to suffer from insufficient coverage and high construction and maintenance cost, whereas fully automatic extraction from corpora or the Web often yields resources of limited quality. Collaboratively built encyclopedias present a viable solution, but do not cover well linguistically oriented knowledge as it is found in dictionaries. That is why we propose extracting linguistic knowledge from Wiktionary, which we achieve by the following three main contributions: (i) We propose the novel multilingual ontology OntoWiktionary that is created by extracting and harmonizing the weakly structured dictionary articles in Wiktionary. A particular challenge in this process is the ambiguity of semantic relations and translations, which we resolve by automatic word sense disambiguation methods. (ii) We automatically align Wiktionary with WordNet 3.0 at the word sense level. The largely complementary information from the two dictionaries yields an aligned resource with higher coverage and an enriched representation of word senses. (iii) We represent Wiktionary according to the ISO standard Lexical Markup Framework, which we adapt to the peculiarities of collaborative dictionaries. This standardized representation is of great importance for fostering the interoperability of resources and hence the dissemination of Wiktionary-based research. To this end, our work presents a foundational step towards the large-scale integrated resource UBY, which facilitates a unified access to a number of standardized dictionaries by means of a shared web interface for human users and an application programming interface for natural language processing applications. A user can, in particular, switch between and combine information from Wiktionary and other dictionaries without completely changing the software. Our final resource and the accompanying datasets and software are publicly available and can be employed for multiple different natural language processing applications. It particularly fills the gap between the small expert-built wordnets and the large amount of encyclopedic knowledge from Wikipedia. We provide a survey of previous works utilizing Wiktionary, and we exemplify the usefulness of our work in two case studies on measuring verb similarity and detecting cross-lingual marketing blunders, which make use of our Wiktionary-based resource and the results of our metalexicographic study. We conclude the thesis by emphasizing the usefulness of collaborative dictionaries when being combined with expert-built resources, which bears much unused potential

    Terminological Methods in Lexicography: Conceptualising, Organising, and Encoding Terms in General Language Dictionaries

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    Os dicionários de língua geral apresentam inconsistências de uniformização e cientificidade no tratamento do conteúdo lexicográfico especializado. Analisando a presença e o tratamento de termos em dicionários de língua geral, propomos um tratamento mais uniforme e cientificamente rigoroso desse conteúdo, considerando também a necessidade de compilar e alinhar futuros recursos lexicais em consonância com padrões interoperáveis. Partimos da premissa de que o tratamento dos itens lexicais, sejam unidades lexicais (palavras em geral) ou unidades terminológicas (termos ou palavras pertencentes a determinados domínios), deve ser diferenciado, e recorremos a métodos terminológicos para tratar os termos dicionarizados. A nossa abordagem assume que a terminologia – na sua dupla dimensão linguística e conceptual – e a lexicografia, como domínios interdisciplinares, podem ser complementares. Assim, apresentamos objetivos teóricos (aperfeiçoamento da metalinguagem e descrição lexicográfica a partir de pressupostos terminológicos) e práticos (representação consistente de dados lexicográficos), que visam facilitar a organização, descrição e modelização consistente de componentes lexicográficos, nomeadamente a hierarquização das etiquetas de domínio, que são marcadores de identificação de léxico especializados. Queremos ainda facilitar a redação de definições, as quais podem ser otimizadas e elaboradas com maior precisão científica ao seguir uma abordagem terminológica no tratamento dos termos. Analisámos os dicionários desenvolvidos por três instituições académicas distintas: a Academia das Ciências de Lisboa, a Real Academia Española e a Académie Française, que representam um valioso legado da tradição lexicográfica académica europeia. A análise inicial inclui um levantamento exaustivo e a comparação das etiquetas de domínio usadas, bem como um debate sobre as opções escolhidas e um estudo comparativo do tratamento dos termos. Elaborámos, depois, uma proposta metodológica para o tratamento de termos em dicionários de língua geral, tomando como exemplo dois domínios, GEOLOGIA e FUTEBOL, extraídos da edição de 2001 do dicionário da Academia das Ciências de Lisboa. Revimos os termos selecionados de acordo com os princípios terminológicos defendidos, dando origem a sentidos especializados revistos/novos para a primeira edição digital deste dicionário. Representamos e anotamos os dados usando as especificações da TEI Lex-0, uma extensão da TEI (Text Encoding Initiative), dedicada à codificação de dados lexicográficos. Destacamos também a importância de ter etiquetas de domínio hierárquicas em vez de uma lista simples de domínios, vantajosas para a organização dos dados, correspondência e possíveis futuros alinhamentos entre diferentes recursos lexicográficos. A investigação revelou que a) os modelos estruturais dos recursos lexicais são complexos e contêm informação de natureza diversa; b) as etiquetas de domínio nos dicionários gerais da língua são planas, desequilibradas, inconsistentes e, muitas vezes, estão desatualizadas, havendo necessidade de as hierarquizar para organizar o conhecimento especializado; c) os critérios adotados para a marcação dos termos e as fórmulas utilizadas na definição são díspares; d) o tratamento dos termos é heterogéneo e formulado de diferentes formas, pelo que o recurso a métodos terminológicos podem ajudar os lexicógrafos a redigir definições; e) a aplicação de métodos terminológicos e lexicográficos interdisciplinares, e também de padrões, é vantajosa porque permite a construção de bases de dados lexicais estruturadas, concetualmente organizadas, apuradas do ponto de vista linguístico e interoperáveis. Em suma, procuramos contribuir para a questão urgente de resolver problemas que afetam a partilha, o alinhamento e vinculação de dados lexicográficos.General language dictionaries show inconsistencies in terms of uniformity and scientificity in the treatment of specialised lexicographic content. By analysing the presence and treatment of terms in general language dictionaries, we propose a more uniform and scientifically rigorous treatment of this content, considering the necessity of compiling and aligning future lexical resources according to interoperable standards. We begin from the premise that the treatment of lexical items, whether lexical units (words in general) or terminological units (terms or words belonging to particular subject fields), must be differentiated, and resort to terminological methods to treat dictionary terms. Our approach assumes that terminology – in its dual dimension, both linguistic and conceptual – and lexicography, as interdisciplinary domains, can be complementary. Thus, we present theoretical (improvement of metalanguage and lexicographic description based on terminological assumptions) and practical (consistent representation of lexicographic data) objectives that aim to facilitate the organisation, description and consistent modelling of lexicographic components, namely the hierarchy of domain labels, as they are specialised lexicon identification markers. We also want to facilitate the drafting of definitions, which can be optimised and elaborated with greater scientific precision by following a terminological approach for the treatment of terms. We analysed the dictionaries developed by three different academic institutions: the Academia das Ciências de Lisboa, the Real Academia Española and the Académie Française, which represent a valuable legacy of the European academic lexicographic tradition. The initial analysis includes an exhaustive survey and comparison of the domain labels used, as well as a debate on the chosen options and a comparative study of the treatment of the terms. We then developed a methodological proposal for the treatment of terms in general language dictionaries, exemplified using terms from two domains, GEOLOGY and FOOTBALL, taken from the 2001 edition of the dictionary of the Academia das Ciências de Lisboa. We revised the selected terms according to the defended terminological principles, giving rise to revised/new specialised meanings for the first digital edition of this dictionary. We represent and annotate the data using the TEI Lex-0 specifications, a TEI (Text Encoding Initiative) subset for encoding lexicographic data. We also highlight the importance of having hierarchical domain labels instead of a simple list of domains, which are beneficial to the data organisation itself, correspondence and possible future alignments between different lexicographic resources. Our investigation revealed the following: a) structural models of lexical resources are complex and contain information of a different nature; b) domain labels in general language dictionaries are flat, unbalanced, inconsistent and often outdated, requiring the need to hierarchise them for organising specialised knowledge; c) the criteria adopted for marking terms and the formulae used in the definition are disparate; d) the treatment of terms is heterogeneous and formulated differently, whereby terminological methods can help lexicographers to draft definitions; e) the application of interdisciplinary terminological and lexicographic methods, and of standards, is advantageous because it allows the construction of structured, conceptually organised, linguistically accurate and interoperable lexical databases. In short, we seek to contribute to the urgent issue of solving problems that affect the sharing, alignment and linking of lexicographic data

    Language technologies for a multilingual Europe

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    This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)

    TC3 III

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    This volume of the series “Translation and Multilingual Natural Language Processing” includes most of the papers presented at the Workshop “Language Technology for a Multilingual Europe”, held at the University of Hamburg on September 27, 2011 in the framework of the conference GSCL 2011 with the topic “Multilingual Resources and Multilingual Applications”, along with several additional contributions. In addition to an overview article on Machine Translation and two contributions on the European initiatives META-NET and Multilingual Web, the volume includes six full research articles. Our intention with this workshop was to bring together various groups concerned with the umbrella topics of multilingualism and language technology, especially multilingual technologies. This encompassed, on the one hand, representatives from research and development in the field of language technologies, and, on the other hand, users from diverse areas such as, among others, industry, administration and funding agencies. The Workshop “Language Technology for a Multilingual Europe” was co-organised by the two GSCL working groups “Text Technology” and “Machine Translation” (http://gscl.info) as well as by META-NET (http://www.meta-net.eu)
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