Претрага
4 items
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Resource-based WordNet Augmentation and Enrichment
In this paper we present an approach to support production of synsets for SerbianWordNet(SerWN)byadjustingPrincetonWordNet(PWN)synsetsusing several bilingual English-Serbian resources. PWN synset definitions were automatically translated and post-edited, if needed, while candidate literals for Serbian synsets were obtained automatically from a list of translational equivalents compiled form bilingual resources. Preliminary results obtained from a setof1248selectedPWNsynsetsshowthattheproducedSerbiansynsetscontain 4024 literals, out of which 2278 were offered by the system we present in this paper, whereas experts added the remaining 1746. Approximately one half of ...Ranka Stanković, Miljana Mladenović, Ivan Obradović, Marko Vitas, Cvetana Krstev. "Resource-based WordNet Augmentation and Enrichment" in Proceedings of the Third International Conference Computational Linguistics in Bulgaria (CLIB 2018), May 27-29, 2018, Sofia, Bulgaria, Sofia : The Institute for Bulgarian Language Prof. Lyubomir Andreychin, Bulgarian Academy of Sciences (2018) M33
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Two approaches to compilation of bilingual multi-word terminology lists from lexical resources
In this paper, we present two approaches and the implemented system for bilingual terminology extraction that rely on an aligned bilingual domain corpus, a terminology extractor for a target language, and a tool for chunk alignment. The two approaches differ in the way terminology for the source language is obtained: the first relies on an existing domain terminology lexicon, while the second one uses a term extraction tool. For both approaches, four experiments were performed with two parameters being ...Branislava Šandrih, Cvetana Krstev, Ranka Stanković. "Two approaches to compilation of bilingual multi-word terminology lists from lexical resources" in Natural Language Engineering, Cambridge University Press (CUP) (2020). https://doi.org/10.1017/S1351324919000615 М21
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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 М53
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Towards Semantic Interoperability: Parallel Corpora as Linked Data Incorporating Named Entity Linking
U radu se prikazuju rezultati istraživanja vezanih za pripremu paralelnih korpusa, fokusirajući se na transformaciju u RDF grafove koristeći NLP Interchange Format (NIF) za lingvističku anotaciju. Pružamo pregled paralelnog korpusa koji je korišćen u ovom studijskom slučaju, kao i proces označavanja delova govora, lematizacije i prepoznavanja imenovanih entiteta (NER). Zatim opisujemo povezivanje imenovanih entiteta (NEL), konverziju podataka u RDF, i uključivanje NIF anotacija. Proizvedene NIF datoteke su evaluirane kroz istraživanje triplestore-a korišćenjem SPARQL upita. Na kraju, razmatra se povezivanje Linked ...paralelni korpusi, povezivanje imenovanih entiteta, prepoznavanje imenovanih entiteta, NER, NEL, povezani podaci, NIF, VikipodaciRanka Stanković, Milica Ikonić Nešić, Olja Perisic, Mihailo Škorić, Olivera Kitanović. "Towards Semantic Interoperability: Parallel Corpora as Linked Data Incorporating Named Entity Linking" in Proceedings of the 9th Workshop on Linked Data in Linguistics @ LREC-COLING 2024, Turin, 20-25 May 2024, ELRA and ICCL (2024) М33