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4 items
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A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment
Sina Ahmadi, John P McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette S Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, [...] Ranka Stanković and others (2020)Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually aligning monolingual dictionaries. The alignment is carried out at sense-level for various resources in 15 languages. Moreover, senses are annotated with possible semantic relationships such as broadness, narrowness, relatedness, and equivalence. In comparison to previous datasets for this task, this dataset covers a wide range of languages ...... 2023-10-14 04:19:54 A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment Sina Ahmadi, John P McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette S Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, [...] Ranka Stanković and others Дигитални репозиторијум ...
... Београду [ДР РГФ] A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment | Sina Ahmadi, John P McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette S Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, [...] Ranka Stanković and others | Proceedings of the 12th ...
... under CC-BY-NC 3232 A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment Sina Ahmadi*, John P. McCrae*, Sanni Nimb1, Fahad Khan3, Monica Monachini3, Bolette S. Pedersen8, Thierry Declerck2,12, Tanja Wissik2, Andrea Bellandi3, Irene Pisani4, Thomas Troelsgård1, Sussi Olsen8, Simon Krek5 ...Sina Ahmadi, John P McCrae, Sanni Nimb, Fahad Khan, Monica Monachini, Bolette S Pedersen, Thierry Declerck, Tanja Wissik, Andrea Bellandi, Irene Pisani, [...] Ranka Stanković and others . "A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment" in Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), Marseille, European Language Resources Association (ELRA) (2020)
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The Dictionary of the Serbian Academy: from the Text to the Lexical Database
In this paper we discuss the project of digitization of the Dictionary of the Serbo-Croatian Standard and Vernacular Language. Scanning and character recognition were a particular challenge, since various non-standard character set encoding was used in the course of the almost 60-year long production of the dictionary. The first aim of the project was to formalize the micro-structure of the dictionary articles in order to parse the digitized text of and transform it into structured data stored in relational lexical database. This approach ...... New Oxford English Dictionary Project at the University of Waterloo (pp. 2-7). UW Centre for the New Oxford English Dictionary. Calzolari, N., Monachini, M., Soria, C. (2013). LMF – Historical Context and Perspectives, in: LMF Lexical Markup Framework, Eds: G. Francopoulo, P. Paroubek, John Wiley ...
... lexical resources and ontologies on the semantic web with lemon. In Extended Semantic Web Conference Springer, Berlin, Heidelberg, pp. 245-259. Monachini, M. & Khan, A. F. (2018). Towards the Construction of a Lexical Data and Technology Ecosystem: The Experience of ILC-CNR. In Proceedings of the ...Ranka Stanković, Rada Stijović, Duško Vitas, Cvetana Krstev, Olga Sabo. "The Dictionary of the Serbian Academy: from the Text to the Lexical Database" in Proceedings of the XVIII EURALEX International Congress: Lexicography in Global Contexts, Ljubljana : Ljubljana University Press, Faculty of Arts (2018)
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Part of Speech Tagging for Serbian language using Natural Language Toolkit
Ranka Stanković, Boro Milovanović (2020)Dok se razvijaju složeni algoritmi za NLP (obrada prirodnog jezika), osnovni zadaci kao što je označavanje ostaju veoma važni i još uvek izazovni. NLTK (Natural Language Toolkit) je moćna Python biblioteka za razvoj programa zasnovanih na NLP-u. Pokušavamo da iskoristimo ovu biblioteku za kreiranje PoS (vrsta reči) oznake za savremeni srpski jezik. Jedanaest različitih modela je kreirano korišćenjem NLTK API-ja za označavanje. Najbolji modeli se transformišu sa Brill tagerom da bi se poboljšala tačnost. Obučili smo modele na označenom ...... of Serbian,” Informatica, vol. 28 no. 4 pp. 431–436, Dec. 2004. [10] M. Gavrilidou, P. Labropoulou, S. Piperidis, V. Giouli, N. Calzolari, M. Monachini, C. Soria, and K. Choukri, “Language Resources Production Models: the Case of the INTERA Multilingual Corpus and Terminology,” Proc. Fifth International ...Ranka Stanković, Boro Milovanović. "Part of Speech Tagging for Serbian language using Natural Language Toolkit" in 7th International Conference on Electrical, Electronic and Computing Engineering IcETRAN 2020, Academic Mind, Belgrade (2020)
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Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian
The training of new tagger models for Serbian is primarily motivated by the enhancement of the existing tagset with the grammatical category of a gender. The harmonization of resources that were manually annotated within different projects over a long period of time was an important task, enabled by the development of tools that support partial automation. The supporting tools take into account different taggers and tagsets. This paper focuses on TreeTagger and spaCy taggers, and the annotation schema alignment ...... european languages. Lan- guage resources and evaluation, 46(1):131–142. Gavrilidou, M., Labropoulou, P., Piperidis, S., Giouli, V., Calzolari, N., Monachini, M., Soria, C., and Choukri, K. (2006). Language resources production models: the case of the intera multilingual corpus and terminology. Politics ...Ranka Stanković, Branislava Šandrih, Cvetana Krstev, Miloš Utvić, Mihailo Škorić. "Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian" in Proceedings of the 12th Language Resources and Evaluation Conference, May Year: 2020, Marseille, France, European Language Resources Association (2020)