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186 items
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Српски језик у дигиталном добу -- The Serbian Language in the Digital Age
Duško Vitas, Ljubomir Popović, Cvetana Krstev, Ivan Obradović, Gordana Pavlović-Lažetić, Mladen Stanojević (2012)... role of Serbian in European information soci- ety and assess the current state of language technology for the Serbian language. 47 3 THE SERBIAN LANGUAGE IN THE EUROPEAN INFORMATION SOCIETY 3.1 GENERAL FACTS Standard Serbian is the standard national language of Serbs and the official language in the ...
... 4 LANGUAGE TECHNOLOGY SUPPORT FOR SERBIAN Language technology is used to develop soware sys- tems designed to handle human language and are there- fore oen called “human language technology”. Human language comes in spoken and written forms. While speech is the oldest and in terms of human evolution ...
... complexity of Serbian and the number of technologies involved in typical language technology applications. In the next chapter, we will present an overview of language technology and its core application areas as well as an evaluation of the current situation of language technology support for Serbian. 57 ...Duško Vitas, Ljubomir Popović, Cvetana Krstev, Ivan Obradović, Gordana Pavlović-Lažetić, Mladen Stanojević. "Српски језик у дигиталном добу -- The Serbian Language in the Digital Age" in META-NET White Paper Series, G. Rehm, H. Uszkoreit (eds.), Springer (2012)
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WS4LR - a Worksation for Lexical Resources
... taTable + target_TextRow + target_TextRowChangeEvent 1695 5. Conclusions Although WS4LR has been used mainly for Serbian language resources, it is by no means language dependent. The only prerequisite is that the resources exist or are being developed according to the described formats and ...
... aligned texts and transducers equally and has already proved very useful for various tasks. Although it has so far been used mainly for Serbian, WS4LR is not language dependent and can be successfully used for resources in other languages provided that they follow the described formats and methodologies ...
... English, Greek, Portuguese, Russian, Thai, Korean, Italian, Spanish, Norwegian, Arabic, German, Polish, Bulgarian, and Serbian. The Intex2 , Unitex3 and Nooj4 systems for natural language processing based on linguistic resources provide for text processing using this type of dictionaries, but offer no ...Cvetana Krstev, Ranka Stanković, Duško Vitas, Ivan Obradović. "WS4LR - a Worksation for Lexical Resources" in Proceedings of the Fifth Interantional Conference on Language Resources and Evaluation, Genoa, Italy, May 2006, ELRA - European Language Resources Association (2006)
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An Italian-Serbian Sentence Aligned Parallel Literary Corpus
This article presents the construction and relevance of an Italian-Serbian sentence-aligned parallel corpus, delving into the aligned sentences in order to facilitate effective translation between the two languages. The parallel corpus serves as a valuable resource for language experts, researchers, and language enthusiasts, fostering a deeper understanding of linguistic nuances and cultural expressions. By bridging the gap between Serbian and Italian, this corpus opens new avenues for cross-cultural communication and collaboration, and ultimately contributes to the improvement of language-related ...Saša Moderc, Ranka Stanković, Aleksandra Tomašević, Mihailo Škorić. "An Italian-Serbian Sentence Aligned Parallel Literary Corpus" in Review of the National Center for Digitization, Belgrade : Faculty of Mathematics, University of Belgrade (2023). https://doi.org/10.5281/zenodo.11203388
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Vebran Web Services for Corpus Query Expansion
Ranka Stanković, Miloš Utvić (2020)U ovom radu se govori o razvoju veb usluga Vebran i njihovoj primeni u poboljšanju pretraživanja korpusa. Veb-servisi Vebran koriste se za konsultovanje spoljnih leksičkih izvora za srpski jezik (uglavnom elektronski morfološki rečnici i srpski Vordnet) i proširivanje korisničkih upita radi dobijanja relevantnijih rezultata iz srpskih korpusa.... Human Language Technology (HLT) Group at the University of Belgrade and the Language Resources and Technologies Society (JeRTeh): – monolingual general corpora: Corpus of Contemporary Serbian (versions SrpKor2003 and SrpKor2013)1 and its subset SrpLemKor2; – SrpEngKor3, aligned English-Serbian corpus ...
... s”) in Serbian using Serbian Latin alphabet Parameter Value examples Description lema sreća Requested lemma X alphOut C Alphabet of the output result C-Cyrillic, L-Latin, A-Aurora, combinations like CL, CA, LA, CLA are allowed lngIn sr language of a given lemma X, by default sr (Serbian) lngOut ...
... Stanković R. and Utvić M., “Vebran Web Service . . . ”, pp. 99–118 Sections 2 and 3 describe language resources for Serbian, corpora that we can search and lexical resources that Natural Language Processing (NLP) applications can consult. Vebran web services and their usage of lexical re- sources ...Ranka Stanković, Miloš Utvić. "Vebran Web Services for Corpus Query Expansion" in Infotheca, Faculty of Philology, University of Belgrade (2020). https://doi.org/10.18485/infotheca.2019.19.2.5
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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 ...... database, language resources, dictionary, Serbian language 1 Introduction The first volume of the Dictionary of the Serbo-Croatian Standard and Vernacular Language (re- ferred to as the Dictionary of Serbian Academy or DSA), prepared and compiled by the Institute for the Serbian Language of the Serbian ...
... 941Lexicography in gLobaL contexts The Dictionary of the Serbian Academy: from the Text to the Lexical Database Ranka Stanković1, Rada Stijović2, Duško Vitas1, Cvetana Krstev1, Olga Sabo2 1University of Belgrade, 2Institute for Serbian Language, Serbian Academy of Sciences and Arts E-mail: ranka.stankovic@rgf ...
... Međunarodni slavistički centar, Beograd, pp. 105-116. [Blueprint for the computerized dictionary of the Serbian language (in Cyrillic)] Acknowledgements This research was partially supported by Serbian Ministry of Education and Science under the grants #III 47003, #178003 and #178009. Powered by TCPDF ...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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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 ...... be taken into consideration and tested in order to find the best solu- tion for Serbian, a highly-inflected language without fixed word order, for instance RNNTagger.9 Since CRF tagger for Serbian and Croatian language obtained the accuracy over 98%, as reported in (Ljubešić et al., 2016), we plan ...
... Conference on Language Resources and Evaluation (LREC 2020), pages 3954–3962 Marseille, 11–16 May 2020 c© European Language Resources Association (ELRA), licensed under CC-BY-NC 3954 Machine Learning and Deep Neural Network-Based Lemmatization and Morphosyntactic Tagging for Serbian Ranka Stanković ...
... on our manually annotated datasets, in order to get a more complete picture of possible solutions for the Serbian language. Once prepared, the models for tagging will be used to tag the Serbian part of ELTeC (European Literary Text Collec- tion) corpus.10 It should be noted that within this action ...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)
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Frequency and Length of Syllables in Serbian
Marija Radojičić, Biljana Lazić, Sebastijan Kaplar, Ranka Stanković, Ivan Obradović, Ján Mačutek, Lívia Leššová (2019)Basic analyses of several properties of syllables (the rank-frequency distribution, the distribution of length, and the relation between length and frequency) in Serbian is presented. The syllabification algorithm used combines the maximum onset principle and the sonority hierarchy. Results indicate that syllables behave similarly to words as far as mathematical models are concerned, but values of parameters in models for syllables are quite different from those for words.... Length of Syllables in Serbian 117 3. Language material Serbian is a South Slavic language. It has the official status in Serbia (exclusively) and in Bosnia and Herzegovina (as one of three languages, together with Bosnian and Croatian), and the status of a minority language in several other countries ...
... laterals (l, lj), a vibrant (r) and semivowels (v, j). The Serbian language uses two alphabets: Latin and Cyrillic. Serbian graphemes are presented in Table 1, first Latin ones, then, in brackets, their Cyrillic equivalents14. Every phoneme in Serbian can be presented by a grapheme or by a digraph, in ...
... countries. Given the scope of our research, we briefly mention the Serbian phonology and orthography; more information on the language can be found e.g. in Browne (1993). The Serbian phonological system consists of 30 phonemes - 5 vowels and 25 consonants, out of which 8 are sonorants (Stanojčić ...Marija Radojičić, Biljana Lazić, Sebastijan Kaplar, Ranka Stanković, Ivan Obradović, Ján Mačutek, Lívia Leššová. "Frequency and Length of Syllables in Serbian" in Glottometrics (2019)
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Contrastive Analysis of Syntax Patterns in Comparable Football Corpora in Spanish and Serbian Languages
Jelena Lazarević, Olivera Kitanović (2024.)Cilj rada je istraživanje kolokabilnosti kao načina na koji se leksičke jedinice povezuju sa rečima iz različitih kategorija, formirajući veće jedinice. Istraživanje semantičkih i sintaksičkih principa ovih kombinacija u španskom i srpskom jeziku fudbala izvedeno je na komparabilnim fudbalskim korpusima SrFudKo i EsFudko, razvijenim u okviru doktorske disertacije Jelene Lazarević pod nazivom: Jezičke odlike diskursa novih medija o fudbalu: kontrastivna analiza na korpusu srpskog i španskog jezika. Korpus fudbala SrFudKo, kreiran na osnovu tekstova o fudbalu sa pet srpskih veb-portala: ...Jelena Lazarević, Olivera Kitanović . "Contrastive Analysis of Syntax Patterns in Comparable Football Corpora in Spanish and Serbian Languages" in South Slavic Languages in the Digital Environment JuDig Book of Abstracts, University of Belgrade - Faculty of Philology, Serbia, November 21-23, 2024, University of Belgrade - Faculty of Philology (2024.)
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The Many Faces of SrpKor
Акроним СрпКор означава фамилију електронских корпуса савременог српског језика чија је изградња почела крајем седамдесетих година прошлога века, а која је постала шире видљива заинтересованој истраживачкој заједници објављивањем његове прве верзије на вебу 2002. године. У овом дугом периоду, посебно пре појаве корисних текстуелних ресурса на вебу, развој корпуса се састојао у прикупљању и обради грађе као и у развоју метода обраде корпуса. Наиме, електронски корпус није само колекција текстова у дигиталном облику (како се то, на пример, наводи ...Duško Vitas, Ranka Stanković, Cvetana Krstev. "The Many Faces of SrpKor" in South Slavic Languages in the Digital Environment JuDig Book of Abstracts, University of Belgrade - Faculty of Philology, Serbia, November 21-23, 2024, University of Belgrade - Faculty of Philology (2024.)
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A Twitter Corpus and Lexicon for Abusive Speech Detection in Serbian
Uvredljivi govor na društvenim medijima, uključujući psovke, pogrdni govor i govor mržnje, dostigao je nivo pandemije. Sistem koji bi bio u stanju da detektuje takve tekstove mogao bi da pomogne da internet i društveni mediji postanu bolji virtuelni prostor sa više poštovanja. Istraživanja i komercijalna primena u ovoj oblasti do sada su bili fokusirani uglavnom na engleski jezik. Ovaj rad predstavlja rad na izgradnji AbCoSER-a, prvog korpusa uvredljivog govora na srpskom jeziku. Korpus se sastoji od 6.436 ručno označenih ...... Although each tweet has a language column, in the majority of cases language of Serbian tweets was marked as und – unidentified – since Twitter cannot reliably recognize the Serbian language. For example, out of 150,000 tweets, only 8,000 were marked as tweets in Serbian, while 120,000 were marked as ...
... should we take when building the corpus of abusive language, several future implications were considered: 1) To the best of our knowledge, AbCoSER (Abusive Corpus for serbian) is the first corpus tackling abusive language phenomenon in the Serbian language; 2) This corpus is to be used to enrich our lexicon ...
... languages such as Serbian. The main contribution of this work is the creation of the AbCoSER, the first abusive speech corpus in Serbian, that will, together with abusive speech lexicon, enable the development of automatic abusive speech detection systems for the Serbian language. In the course of this ...Danka Jokić, Ranka Stanković, Cvetana Krstev, Branislava Šandrih. "A Twitter Corpus and Lexicon for Abusive Speech Detection in Serbian" in 3rd Conference on Language, Data and Knowledge (LDK 2021), MDPI AG (2021). https://doi.org/10.4230/OASIcs.LDK.2021.13
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SrpELTeC: A Serbian Literary Corpus for Distant Reading
U članku je predstavljen SrpELTeC, korpus razvijen u okviru akcije COST Distant Reading for European Literary History (CA16204). Svi romani u SrpELTeC-u su odabrani, pripremljeni i obeleženi korišćenjem zajedničkih principa uspostavljenih za sve jezičke zbirke u Evropskoj zbirci književnog teksta (ELTeC). Navedeni su izazovi i rešenja u pripremi SrpELTeC od nule. Svi romani su ručno kodirani u TEI sa bogatim metapodacima i strukturnim napomenama. Automatska anotacija je uključivala POS-označavanje, lematizaciju i imenovane entitete, oslanjajući se na resurse za obradu ...digital humanities, Serbian literature, text corpora, distant reading , linked data, named entity recognition, text analyticsRanka Stanković, Cvetana Krstev, Duško Vitas. "SrpELTeC: A Serbian Literary Corpus for Distant Reading" in Primerjalna književnost, Research Centre of the Slovenian Academy of Sciences and Arts (2024). https://doi.org/10.3986/pkn.v47.i2.03
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Social-Emo.Sr: Emotional Multi-Label Categorization of Conversational Messages from Social Networks X and Reddit
U digitalnom okruženju južnoslovenskih jezika, analiza emocija u tekstovima na društvenim mrežama postaje sve važnija za razumevanje javnog mnjenja, kreiranje personalizovanog sadržaja i analizu međusobnih interakcija korisnika. U okviru ovog rada predstavljamo detaljnu metodologiju i rezultate označavanja korpusa na srpskom jeziku prema Plutčikovom modelu kategorizacije, koji prepoznaje osam osnovnih emocionalnih kategorija, kao što su radost, tuga, bes, strah, poverenje, gađenje, iščekivanje i iznenađenje. Cilj istraživanja je da se analizira emocionalni sadržaj tekstova preuzetih sa društvenih mreža X (nekada Twitter) ...Milena Šošić, Ranka Stanković, Jelena Graovac. "Social-Emo.Sr: Emotional Multi-Label Categorization of Conversational Messages from Social Networks X and Reddit" in South Slavic Languages in the Digital Environment JuDig Book of Abstracts, University of Belgrade - Faculty of Philology, Serbia, November 21-23, 2024., University of Belgrade - Faculty of Philology (2024)
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Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model
Ova studija predstavlja analizu sentimenta srpskih starih romana iz perioda 1840-1920, koristeći veliki jezički model (LLM) Mistral za tehniku učenja sa zasnovani na takozvanim "zero" i "few-shot" pokušajima. Glavni pristup uvodi inovacije osmišljavanjem istraživačkih upita (promptova) uključuju tekst sa uputstvom za klasifikaciju bez primera i na osnovu nekoliko primera, omogućavajući jezičkom modelu da klasifikuje osećanja u pozitivne, negativne ili objektivne kategorije. Ova metodologija ima za cilj da pojednostavi analizu osećanja ograničavanjem odgovora, čime se povećava preciznost ...Milica Ikonić Nešić, Saša Petalinkar, Mihailo Škorić, Ranka Stanković, Biljana Rujević. "Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model" in In Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024), BAS (2024)
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Речници у дигиталном добу - информатичка подршка за српски језик
Биљана Рујевић (2022)Морфолошки речници српског језика представљају електронски језички ресурс који има значајну историју развоја и коришћења за потребе обраде природних језика. С обзиром на то да су чувани у облику датотека чији је број нарастао па је самим тим управљање речницима постало отежано јавила се потреба за смештањем информација из речника у облик лексикографске базе. Како би се омогућио симултани рад на развоју речника за више корисника јавила се потреба за веб-апликацијом заснованој на лексикографској бази. Како би се размотриле ...Биљана Рујевић. Речници у дигиталном добу - информатичка подршка за српски језик, Београд : [Б. Рујевић], 2022
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Production of morphological dictionaries of multi-word units using a multipurpose tool
The development of a comprehensive morphological dictionary of multi-word units for Serbian is a very demanding task, due to the complexity of Serbian morphology. Manual production of such a dictionary proved to be extremely time-consuming. In this paper we present a procedure that automatically produces dictionary lemmas for a given list of multi-word units. To accomplish this task the procedure relies on data in e-dictionaries of Serbian simple words, which are already well developed. We also offer an evaluation ...electronic dictionary, Serbian, morphology, inflection, multi-word units, noun phrases, query expansion... scratch. Serbian is, however, like all Slavic languages a highly inflectional language and such a shortcut procedure cannot be applied. We will illustrate this with one example. The nominal MWU petokraka zvezda ‘five-pointed star’ consists of an adjective followed by a noun, which in Serbian is the ...
... e- dictionaries of Serbian simple words. We present an evaluation of the performance of this functionality, and hence of our procedure, obtained from experiments on two types of data. Finally, we discuss some further possible applications of our procedure and LeXimir in language processing tasks. I ...
... I. INTRODUCTION MORPHOLOGICAL electronic dictionaries of Serbian for natural language processing (NLP) are being de- veloped for many years now. Their development follows the methodology and format (known as DELAS/DELAF) pre- sented for French in [1]. E-dictionaries in the same format have been ...Ranka Stanković, Ivan Obradović, Cvetana Krstev, Duško Vitas. "Production of morphological dictionaries of multi-word units using a multipurpose tool" in Proceedings of the Computational Linguistics-Applications Conference, October 2011, Jachranka, Poland, Jachranka, Poland : PTI - Polish Information Processing Society (2011)
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Automatic construction of a morphological dictionary of multi-word units
The development of a comprehensive morphological dictionary of multi-word units for Serbian is a very demanding task, due to the complexity of Serbian morphology. Manual production of such a dictionary proved to be extremely time-consuming. In this paper we present a procedure that automatically produces dictionary lemmas for a given list of multi-word units. To accomplish this task the procedure relies on data in e-dictionaries of Serbian simple words, which are already well developed. We also offer an evaluation ...electronic dictionary, Serbian, morphology, inflection, multiwordn units, noun phrases, query expansion... for other languages. Key words: electronic dictionary, Serbian, morphology, inflection, multi- word units, noun phrases, query expansion 1 Introduction We have been developing morphological electronic dictionaries of Serbian for natural language processing for many years now. Our e-dictionaries follow ...
... Krstev, C.: Processing of Serbian - Automata, Texts and Electronic Dictionaries. Faculty of Philology, University of Belgrade, Belgrade (2008) 3. Savary, A.: Computational Inflection of Multi-Word Units - A Contrastive Study of Lexical Approaches. Linguistic Issues in Language Technologies 1 (2008) 4 ...
... In: 6th LREC, Marrakech, Marocco (2008) 7. Jacquemin, C.: Spotting and Discovering Terms through Natural Language Pro- cessing. MIT Press (2001) 8. Laporte, E.: Lexicons and Grammars for Language Processing: Industrial or Hand- crafted Products? In Rezende, L.M., da Silva, B.C.D., Barbosa, J.B., eds ...Cvetana Krstev, Ranka Stanković, Ivan Obradović, Duško Vitas, Miloš Utvić. "Automatic construction of a morphological dictionary of multi-word units" in Lecture Notes in Computer Science 6233, Advances in Natural Language Processing, Proceedings of the 7thInternational Conference on NLP, IceTAL 2010, Reykjavik, Iceland, August 2010, Springer (2010): 226-237. https://doi.org/10.1007/978-3-642-14770-8_26
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Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names
In this paper we present a rule- and lexicon-based system for the recognition of Named Entities (NE) in Serbian news paper texts that was used to prepare a gold standard annotated with personal names. It was further used to prepare training sets for four different levels of annota tion, which were further used to train two Named Entity Recognition (NER) sys tems: Stanford and spaCy. All obtained models, together with a rule- and lexicon based system were evaluated on ...... rs Proceedings of Recent Advances in Natural Language Processing, pages 1060–1068, Varna, Bulgaria, Sep 2–4, 2019. https://doi.org/10.26615/978-954-452-056-4_122 1060 Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names Branislava Šandrih ...
... implementation of a Named Entity Recog- nizer by the Stanford Natural Language Process- ing group. It is also known as CRFClassifier, since 6Training NER in spaCy, https://spacy.io/usage/training#ner 7Visualization of SPACY NER for Serbian, http://ner.jerteh.rs/ 1063 PERS_1 PERS_3 PERS_4 PERS_9 m.persName ...
... Resources and Evaluation (LREC’02). European Language Resources Association (ELRA), Las Palmas, Canary Islands - Spain. http://www.lrec- conf.org/proceedings/lrec2002/pdf/120.pdf. Serbian NER team. 2019. NER&Beyond. http:// nerbeyond.jerteh.rs/. Sameer Singh, Dustin Hillard, and Chris Leggetter. 2010. ...Branislava Šandrih, Cvetana Krstev, Ranka Stanković. "Development and Evaluation of Three Named Entity Recognition Systems for Serbian - The Case of Personal Names" in Proceedings - Natural Language Processing in a Deep Learning World, Incoma Ltd., Shoumen, Bulgaria (2019). https://doi.org/10.26615/978-954-452-056-4_122
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FrameNet Lexical Database: Presenting a Few Frames Within the Risk Domain
U radu se daje kratak prikaz teorije semantike okvira, na kojoj je zasnovana leksička baza Frejmnet. Predstavljena je koncepcija ove mreže, kao i mogućnosti njene primene. Predstavljena je i leksička analiza koja se primenjuje u projektu izrade Frejmneta i ukazano na razlike između analize zasnovane na okviru u odnosu na analizu zasnovanu na reči. Zatim je prikazano nekoliko povezanih okvira koje prizivaju reči iz domena rizika. U radu je predstavljena i platforma NLTК pomoću koje se mogu koristiti ...... included. KEYWORDS: Serbian language, frame semantics, FrameNet, risk scenario, mining corpus, natural language processing. PAPER SUBMITTED: 15 July 2021 PAPER ACCEPTED: 6 September 2021 Aleksandra Marković aleksan- dra.markovic@isj.sanu.ac.rs Institute for Serbian Language, SASA Belgrade, Serbia ...
... frames and their elements, based on the data from English language corpora, and translated them into Serbian in order to illustrate the way of presenting data in FrameNet. It is our hope that we will soon get a chance to illustrate frames using Serbian corpus data. 16 Infotheca Vol. 21, No. 1, September ...
... pp. 7–33 by members of the JeRTeh Society for Language Resources and Technolo- gies.22 A Treegger model for Serbian was trained for tagging (Krstev and Vitas 2005; Utvic 2011), (Stanković et al. 2020, 3957) using a manually an- notated corpus of Serbian morphological dictionaries (Krstev 2008). Figure ...Aleksandra Marković, Ranka Stanković, Natalija Tomić, Olivera Kitanović. "FrameNet Lexical Database: Presenting a Few Frames Within the Risk Domain" in Infotheca, Faculty of Philology, University of Belgrade (2021). https://doi.org/10.18485/infotheca.2021.21.1.1
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SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian
Ranka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković (2019)У овом раду представљамо модел за избор добрих примера за речник српског језика и развој иницијалних компоненти модела. Метода која се користи заснива се на детаљној анализи различитих лексичких и синтактичких карактеристика у корпусу састављених од примера из пет дигитализованих свезака речника САНУ. Почетни скуп функција био је инспирисан сличним приступом и за друге језике. Дистрибуција карактеристика примера из овог корпуса упоређује се са карактеристиком дистрибуције узорака реченица ексцерпираних из корпуса који садрже различите текстове. Анализа је показала да ...Српски, добри примери из речника, аутоматизација израде речника, издвајање својстава, Машинско учење... of the Serbian language. The approach was motivated by the need for modernization of the dictionary-making process for the dictionary of the Serbian Academy of Sciences and Arts (SASA), a large monolingual thesaurus of Serbian, as well as for the production of new dictionaries of Serbian. The SASA ...
... by type of lexis/language (labelled with DSS for standard Serbian and DNS for non- standard Serbian) and 3) by part of speech (POS) of the headword/keyword (N – nouns, V – verbs, A – adjectives, ADV – adverbs and X – other). DSS partition contains sentences in contemporary language with examples that ...
... Blueprint for the computerized dictionary of the Serbian language [Nacrt za informatizovani rečnik srpskog jezika]. Naučni sastanak slavista u Vukove dane, 44(3), pp. 105–116. (In Serbian, Cyrillic.) Vitas, D. & Krstev, C. (2012). Processing of Corpora of Serbian Using Electronic Dictionaries. Prace F ...Ranka Stanković, Branislava Šandrih, Rada Stijović, Cvetana Krstev, Duško Vitas, Aleksandra Marković. "SASA Dictionary as the Gold Standard for Good Dictionary Examples for Serbian" in Electronic lexicography in the 21st century. Proceedings of the eLex 2019 conference , Lexical Computing CZ, s.r.o. (2019)
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Аутоматска екстракција дефиниција – допринос убрзању израде речника
дескриптивни речници, метаанализа лексикографских дефиниција, аутоматска екстракција дефиниција, електронски речници, српски језикРада Стијовић, Цветана Крстев, Ранка Станковић. "Аутоматска екстракција дефиниција – допринос убрзању израде речника" in Лексикологија и лексикографија у светлу актуелних проблема, Институт за српски језик САНУ (2021)