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Conceptual Modeling of Events Based on One-Category Ontology
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In: ISSN: 1738-7906 ; International Journal of Computer Science and Network Security ; https://hal.archives-ouvertes.fr/hal-03593416 ; International Journal of Computer Science and Network Security, International Journal of Computer Science and Network Security, 2022, 22 (3) (2022)
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Analysis of Destination Images in the Emerging Ski Market: The Case Study in the Host City of the 2022 Beijing Winter Olympic Games
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In: Sustainability; Volume 14; Issue 1; Pages: 555 (2022)
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Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models
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In: Applied Sciences; Volume 12; Issue 1; Pages: 491 (2022)
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Abstract:
The paper presents the full-size Russian corpus of Internet users’ reviews on medicines with complex named entity recognition (NER) labeling of pharmaceutically relevant entities. We evaluate the accuracy levels reached on this corpus by a set of advanced deep learning neural networks for extracting mentions of these entities. The corpus markup includes mentions of the following entities: medication (33,005 mentions), adverse drug reaction (1778), disease (17,403), and note (4490). Two of them—medication and disease—include a set of attributes. A part of the corpus has a coreference annotation with 1560 coreference chains in 300 documents. A multi-label model based on a language model and a set of features has been developed for recognizing entities of the presented corpus. We analyze how the choice of different model components affects the entity recognition accuracy. Those components include methods for vector representation of words, types of language models pre-trained for the Russian language, ways of text normalization, and other pre-processing methods. The sufficient size of our corpus allows us to study the effects of particularities of annotation and entity balancing. We compare our corpus to existing ones by the occurrences of entities of different types and show that balancing the corpus by the number of texts with and without adverse drug event (ADR) mentions improves the ADR recognition accuracy with no notable decline in the accuracy of detecting entities of other types. As a result, the state of the art for the pharmacological entity extraction task for the Russian language is established on a full-size labeled corpus. For the ADR entity type, the accuracy achieved is 61.1% by the F1-exact metric, which is on par with the accuracy level for other language corpora with similar characteristics and ADR representativeness. The accuracy of the coreference relation extraction evaluated on our corpus is 71%, which is higher than the results achieved on the other Russian-language corpora.
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Keyword:
adverse drug events; annotated corpus; coreference relation extraction; deep learning; information extraction; language models; machine learning; MESHRUS; named entity recognition; neural networks; pharmacovigilance; social media; UMLS
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URL: https://doi.org/10.3390/app12010491
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Writing and Linguistics News
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In: Writing & Linguistics News (2022)
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The role of changes in the segmentation of narrated events: looking at the sign languages ; O papel das mudanças na segmentação de eventos narrados : um olhar para as línguas de sinais
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In: Domínios de Lingu@gem; Vol. 16 No. 1 (2022): Número Atemático; 255-297 ; Domínios de Lingu@gem; v. 16 n. 1 (2022): Número Atemático; 255-297 ; 1980-5799 (2022)
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Northern Tornadoes Project. Annual Report 2021 v2
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In: Project Reports (2022)
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On event-denoting deadjectival nominalizations
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In: ISSN: 0167-6318 ; EISSN: 1613-3676 ; Linguistic Review ; https://hal.archives-ouvertes.fr/hal-03503166 ; Linguistic Review, De Gruyter, 2021, 38 (2), pp.191-231. ⟨10.1515/tlr-2021-2063⟩ (2021)
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Asymmetries in Path expression in Ye’kwana
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In: ISSN: 0378-4177 ; Studies in Language ; https://hal.archives-ouvertes.fr/hal-03113498 ; Studies in Language, John Benjamins Publishing, In press, pp.sl.18023.cac ; https://benjamins.com/catalog/sl.18023.cac (2021)
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Reply to Comment by Mandel et al. on “Numerically Bounded Linguistic Probability Schemes Are Unlikely to Communicate Uncertainty Effectively”
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In: Earth's Future, vol 9, iss 1 (2021)
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Motion Events in Nepali ; L'expression des événements de mouvement en népalais
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In: https://tel.archives-ouvertes.fr/tel-03406099 ; Linguistics. Université de Lyon, 2021. English. ⟨NNT : 2021LYSE2032⟩ (2021)
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Chapter 2. Talking about giving
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In: Give Constructions across Languages ; https://hal-univ-paris3.archives-ouvertes.fr/hal-03328866 ; ed. Myriam Bouveret. Give Constructions across Languages, 29, pp.55-72, 2021, Constructional Approaches to Language, 9789027260154. ⟨10.1075/cal.29.02mor⟩ ; https://www.jbe-platform.com/content/series/1573594x (2021)
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An inquisitive account of wh-questions through event semantics
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In: LACL 2021 - Logical Aspects of Computational Linguistics ; https://hal.inria.fr/hal-03541222 ; LACL 2021 - Logical Aspects of Computational Linguistics, Dec 2021, Montpellier (online), France (2021)
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Linguistic expression and conceptual representation of motion events in Arabic and English ... : Evidence from monolinguals and bilinguals ...
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How children attend to events before speaking: crosslinguistic evidence from the motion domain
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In: Glossa: a journal of general linguistics; Vol 6, No 1 (2021); 28 ; 2397-1835 (2021)
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Do thus: an investigation into anaphoric event reference
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In: Glossa: a journal of general linguistics; Vol 6, No 1 (2021); 78 ; 2397-1835 (2021)
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Fine-Grained Implicit Sentiment in Financial News: Uncovering Hidden Bulls and Bears
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In: Electronics ; Volume 10 ; Issue 20 (2021)
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Demonstratives as bundlers of conceptual structure
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In: Glossa: a journal of general linguistics; Vol 6, No 1 (2021); 33 ; 2397-1835 (2021)
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Eventi dal vivo e accessibilità: uno studio di caso sul respeaking interlinguistico ...
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Asymmetries in Path expression in Ye’kwana
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In: ISSN: 0378-4177 ; Studies in Language ; https://hal.archives-ouvertes.fr/hal-03113498 ; Studies in Language, John Benjamins Publishing, 2021, 45 (1), pp.203-234 ; https://benjamins.com/catalog/sl.18023.cac (2021)
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UCD-CS at W-NUT 2020 Shared Task-3: A Text to Text Approach for COVID-19 Event Extraction on Social Media
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