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Упит dcterms_creator_txt:Petya Osenova

3 items

  • Multiword Expressions between the Corpus and the Lexicon: Universality, Idiosyncrasy and the Lexicon-Corpus Interface

    Verginica Barbu Mititelu, Voula Giouli, Kilian Evang, Daniel Zeman, Petya Osenova, Carole Tiberius, Simon Krek, Stella Markantonatou, Ivelina Stoyanova, Ranka Stankovic, Christian Chiarcos (2024)
    Predstavljamo trenutne aktivnosti na definisanju interfejsa leksikona i korpusa koji će služiti kao referenca u prikazu polileksemskih jedinica - višečlanih izraza - (različitih tipova - imenskih, glagolskih, itd.) u specijalizovanim leksikonima i povezivanju ovih unosa sa njihovim pojavljivanjima u korpusima. Konačni cilj je korišćenje ovakvih resursa za automatsko identifikovanje višečlanih izraza u tekstu. Uključivanje nekoliko prirodnih jezika ima za cilj univerzalnost rešenja koje nije usredsređeno na određeni jezik, kao i prilagođavanje idiosinkrazijama. Raspravljaju se izazovi u leksikografskom opisu višerečnih ...
    multiword expression lexicon, corpus, proof-of-concept lexicon encoding

  • 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 ...
    lexical semantic resources, sense alignment, lexicography, language resource
    ... lexical coverage. In Proceedings of the Interna- tional FrameNet Workshop at LREC 2018: Multilingual FrameNets and Constructions, pages 51–55. Osenova, P. and Simov, K. (2017). Challenges behind the data-driven bulgarian wordnet (bultreebank bulgarian wordnet). In John P. McCrae, et al., editors ...
    ... semantic parsing. In International conference on intelli- gent text processing and computational linguistics, pages 100–111. Springer. Simov, K., Osenova, P., Laskova, L., Radev, I., and Kancheva, Z. (2019). Aligning the bulgarian btb word- net with the bulgarian wikipedia. In Christiane Fell- baum ...
    ... Cillessen7, David Lindemann14, Mikel Alonso14, Ana Salgado15 José Luis Sancho16, Rafael-J. Ureña-Ruiz16, Jordi Porta Zamorano16, Kiril Simov17, Petya Osenova17, Zara Kancheva17, Ivaylo Radev17, Ranka Stanković18, Andrej Perdih19, Dejan Gabrovšek19 *Insight Centre for Data Analytics, National ...

  • Advancing Sentiment Analysis in Serbian Literature: A Zero and Few-Shot Learning Approach Using the Mistral Model

    Milica Ikonić Nešić, Saša Petalinkar, Mihailo Škorić, Ranka Stanković, Biljana Rujević (2024)
    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 ...
    zero-shot, few-shot, sentiment, Serbian, Mistral model