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Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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2
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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3
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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4
Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers ...
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5
Deep learning for sentence clustering in essay grading support ...
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6
Universal Dependencies 2.7
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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7
Universal Dependencies 2.6
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020
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8
Towards Fully Bilingual Deep Language Modeling ...
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9
The birth of Romanian BERT ...
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10
WikiBERT models: deep transfer learning for many languages ...
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11
Exploring Cross-sentence Contexts for Named Entity Recognition with BERT ...
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12
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ...
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13
Dependency parsing of biomedical text with BERT
In: BMC Bioinformatics (2020)
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14
Universal Dependencies 2.5
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019
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15
Universal Dependencies 2.4
Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019
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16
Multilingual is not enough: BERT for Finnish ...
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17
A neural classification method for supporting the creation of BioVerbNet ...
Chiu, Billy; Majewska, Olga; Pyysalo, Sampo. - : Figshare, 2019
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18
A neural classification method for supporting the creation of BioVerbNet ...
Abstract: Abstract Background VerbNet, an extensive computational verb lexicon for English, has proved useful for supporting a wide range of Natural Language Processing tasks requiring information about the behaviour and meaning of verbs. Biomedical text processing and mining could benefit from a similar resource. We take the first step towards the development of BioVerbNet: A VerbNet specifically aimed at describing verbs in the area of biomedicine. Because VerbNet-style classification is extremely time consuming, we start from a small manual classification of biomedical verbs and apply a state-of-the-art neural representation model, specifically developed for class-based optimization, to expand the classification with new verbs, using all the PubMed abstracts and the full articles in the PubMed Central Open Access subset as data. Results Direct evaluation of the resulting classification against BioSimVerb (verb similarity judgement data in biomedicine) shows promising results when representation learning is ...
Keyword: 69999 Biological Sciences not elsewhere classified; 80699 Information Systems not elsewhere classified; FOS Biological sciences; FOS Computer and information sciences; Plant Biology; Science Policy; Space Science
URL: https://dx.doi.org/10.6084/m9.figshare.c.4372358.v1
https://springernature.figshare.com/collections/A_neural_classification_method_for_supporting_the_creation_of_BioVerbNet/4372358/1
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19
A neural classification method for supporting the creation of BioVerbNet ...
Chiu, Billy; Majewska, Olga; Pyysalo, Sampo. - : Apollo - University of Cambridge Repository, 2019
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20
A Neural Classification Method for Supporting the Creation of BioVerbNet ...
Chiu, Hon Wing; Majewska, Olga; Pyysalo, Sampo. - : Apollo - University of Cambridge Repository, 2019
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