A neural classification method for supporting the creation of BioVerbNet

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 verb class-based contexts. Human validation by linguists and biologists reveals that the automatically expanded classification is highly accurate. Including novel, valid member verbs and classes, our method can be used to facilitate cost-effective development of BioVerbNet. Conclusion This work constitutes the first effort on applying a state-of-the-art architecture for neural representation learning to biomedical verb classification. While we discuss future optimization of the method, our promising results suggest that the automatic classification released with this article can be used to readily support application tasks in biomedicine

Linguistic Variation Issues: Case and Agreement in Northern Russian Participial Constructions

This study offers a novel approach to a longstanding problem in Slavic Linguistics, the formal representation of the Northern Russian participial constructions in -n(o)/-t(o). Unlike previous works, the methodological stance adopted by the author focuses on singling out all the relevant patterns of variation and on pursuing a unified explanation for them. The key to the solution of the puzzle is the idea that the participial affix -n-/-t- and the agreement inflections are not just pieces of morphology inserted post-syntactically, but true heads that enter the computation and are able to manipulate the argumental roles of the verb and to check the EPP. The author’s proposal is properly framed in the context of current debate on interlanguage variation

Semantic verb classes in Tima (Niger-Congo)

The dissertation explores the correlations between the lexical meaning of verbs and their morphosyntactic behavior in terms of valency alternation patterns in the Niger-Congo language Tima spoken in Sudan