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A sentiment-annotated dataset of English causal connectives ...
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Disambiguation of Potentially Idiomatic Expressions with Contextual Embeddings ...
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Abstract:
The majority of multiword expressions can be interpreted as figuratively or literally in different contexts which pose challenges in a number of downstream tasks. Most previous work deals with this ambiguity following the observation that MWEs with different usages occur in distinctly different contexts. Following this insight, we explore the usefulness of contextual embeddings by means of both supervised and unsupervised classification. The results show that in the supervised setting, the state-of-the-art can be substantially improved for all expressions in the experiments. The unsupervised classification, similarly, yields very impressive results, comparing favorably to the supervised classifier for the majority of the expressions. We also show that multilingual contextual embeddings can also be employed for this task without leading to any significant loss in performance; hence, the proposed methodology has the potential to be extended to a number of languages. ...
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Keyword:
Computer and Information Science; Natural Language Processing; Neural Network
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URL: https://underline.io/lecture/6502-disambiguation-of-potentially-idiomatic-expressions-with-contextual-embeddings https://dx.doi.org/10.48448/b63s-3v67
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What Do Language Representations Really Represent?
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In: Bjerva, Johannes; Östling, Robert; Veiga, Maria Han; Tiedemann, Jörg; Augenstein, Isabelle (2019). What Do Language Representations Really Represent? Computational Linguistics, 45(2):381-389. (2019)
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Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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Visual Iconicity Across Sign Languages: Large-Scale Automated Video Analysis of Iconic Articulators and Locations
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Universal Dependencies 2.1
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In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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Articulation rate in Swedish child-directed speech increases as a function of the age of the child even when surprisal is controlled for ...
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