Papers by Iva Marinova
The Bulgarian Event Corpus: Overview and Initial NER Experiments (2022.lrec-1)
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| Challenge: | Initial experiments on standard NER task due to complexity of dataset and rich NE annotation scheme are promising with respect to some labels and give insights on handling better other ones. |
| Approach: | They describe a Bulgarian Event Corpus (BEC) that includes named entities and events with their roles. |
| Outcome: | The proposed corpus is multi-domain and oriented towards Social Sciences and Humanities (SSH) it includes named entities and events with their roles. |
Reconstructing NER Corpora: a Case Study on Bulgarian (2020.lrec-1)
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| Challenge: | Named Entity Recognition (NER) and Named Enel Linking (NEL) are two related tasks that are under-resourced for the Slavic languages. |
| Approach: | They propose to use deep learning methods to improve a Named Entity Recognition corpus and to predict and annotate new types in a test corpus. |
| Outcome: | The proposed model improves a type-based Named Entity Recognition (NER) training corpus and predicts and annotates new types in a test corpus. |
SM-FEEL-BG - the First Bulgarian Datasets and Classifiers for Detecting Feelings, Emotions, and Sentiments of Bulgarian Social Media Text (2024.lrec-main)
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Irina Temnikova, Iva Marinova, Silvia Gargova, Ruslana Margova, Alexander Komarov, Tsvetelina Stefanova, Veneta Kireva, Dimana Vyatrova, Nevena Grigorova, Yordan Mandevski, Stefan Minkov
| Challenge: | SM-FEEL-BG is the first Bulgarian-language package for emotion detection and sentiment analysis. |
| Approach: | They introduce SM-FEEL-BG, a Bulgarian-language package that contains 6 datasets with Social Media (SM) texts with emotion, feeling, and sentiment labels and 4 classifiers trained on them. |
| Outcome: | The proposed package is the first to be released in Bulgarian and is available for free. |