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A Neural Classification Method for Supporting the Creation of BioVerbNet ...
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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 performed using ... : This work is supported by the Medical Research Council [grant number MR/M013049/1], the ERC Consolidator Grant LEXICAL [grant number 648909], the ESRC Doctoral Fellowship [grant number ES/J500033/1] and the Defense Advanced Research Projects Agency [DARPA 15-18-CwC-FP-032] ...
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Keyword:
representation learning; verb lexicon
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URL: https://www.repository.cam.ac.uk/handle/1810/289364
https://dx.doi.org/10.17863/cam.36611
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A Neural Classification Method for Supporting the Creation of BioVerbNet
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