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Data for Training and Evaluating Metadata Extraction Models based on 15 Thousand Cyrillic Script Publications ...
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Token-level Multilingual Epidemic Dataset for Event Extraction ...
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Token-level Multilingual Epidemic Dataset for Event Extraction ...
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Data for Training and Evaluating Metadata Extraction Models based on 15 Thousand Cyrillic Script Publications ...
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Abstract:
Description Data for training and evaluating sequence labeling models for metadata extraction based on 15,553 Cyrillic script language papers spanning 27 years and three languages. For each paper, ground truth sequence labeling output is provided in TEI format and as annotated plain text. The code used for creating and evaluating the data set can be found on GitHub. For citing , you can refer to our paper introducing the data set: @inproceedings{kssf-2021-cyrillic, title = {{Bootstrapping Multilingual Metadata Extraction: A Showcase in Cyrillic}}, author = {Krause, Johan and Shapiro, Igor and Saier, Tarek and F{\"a}rber, Michael}, booktitle = {Proceedings of the Second Workshop on Scholarly Document Processing}, year = {2021} } ...
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Keyword:
bulgarian; cyrillic; metadata extraction; russian; scholarly data; sequence labeling; ukranian
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URL: https://dx.doi.org/10.5281/zenodo.4708696 https://zenodo.org/record/4708696
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HTLinker: A Head-to-Tail Linker for Nested Named Entity Recognition
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In: Symmetry ; Volume 13 ; Issue 9 (2021)
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A Deep Neural Network-Based Model for Named Entity Recognition for Hindi Language
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In: ETSU Faculty Works (2020)
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NAT: Noise-Aware Training for Robust Neural Sequence Labeling
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In: Fraunhofer IAIS (2020)
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Modeling a label global context for sequence tagging in recurrent neural networks ; Modélisation d'un contexte global d'étiquettes pour l'étiquetage de séquences dans les réseaux neuronaux récurrents
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In: Journée commune AFIA-ATALA sur le Traitement Automatique des Langues et l’Intelligence Artificielle pendant la onzième édition de la plate-forme Intelligence Artificielle (PFIA 2018) ; https://hal.archives-ouvertes.fr/hal-02002111 ; Journée commune AFIA-ATALA sur le Traitement Automatique des Langues et l’Intelligence Artificielle pendant la onzième édition de la plate-forme Intelligence Artificielle (PFIA 2018), Jul 2018, Nancy, France ; https://pfia2018.loria.fr/journee-tal/ (2018)
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A Simple and Effective biLSTM Approach to Aspect-Based Sentiment Analysis in Social Media Customer Feedback
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In: Clematide, Simon (2018). A Simple and Effective biLSTM Approach to Aspect-Based Sentiment Analysis in Social Media Customer Feedback. In: Barbaresi, Adrien; Biber, Hanno; Neubarth, Friedrich; Osswald, Rainer. 14th Conference on Natural Language Processing - KONVENS 2018. Vienna: Verlag der Österreichischen Akademie der Wissenschaften, 29-33. (2018)
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Semi-Markov models for sequence segmentation
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In: Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2007) ; http://www.aclweb.org/anthology-new/D/D07/D07-1.pdf (2015)
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Elephant: Sequence Labeling for Word and Sentence Segmentation
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In: EMNLP 2013 ; https://hal.archives-ouvertes.fr/hal-01344500 ; EMNLP 2013, Oct 2013, Seattle, United States (2013)
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Unsupervised Large-Vocabulary Word Sense Disambiguation with Graph-based Algorithms for Sequence Data Labeling
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In: Joint Conference on Human Language Technology / Empirical Methods in Natural Language Processing (HLT/EMNLP), 2005, Vancouver, British Columbia, Canada (2005)
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Feature-Rich Information Extraction for the Technical Trend-Map Creation
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In: http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings8/NTCIR/04-NTCIR8-PATMN-NishiyamaR.pdf
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