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A Self-Paced Reading Study on Processing Constructions with Different Degrees of Compositionality
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In: The 35th Annual Conference on Human Sentence Processing ; https://hal.archives-ouvertes.fr/hal-03620795 ; The 35th Annual Conference on Human Sentence Processing, Mar 2022, UC Santa Cruz, United States (2022)
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Does BERT really agree ? Fine-grained Analysis of Lexical Dependence on a Syntactic Task ...
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Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge
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In: Proceedings of *SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics ; https://hal.archives-ouvertes.fr/hal-03312774 ; SEM 2021: The Tenth Joint Conference on Lexical and Computational Semantics, Aug 2021, Online, France. pp.1-11, ⟨10.18653/v1/2021.starsem-1.1⟩ (2021)
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Not all arguments are processed equally: a distributional model of argument complexity
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In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.archives-ouvertes.fr/hal-03533181 ; Language Resources and Evaluation, Springer Verlag, 2021, 55 (4), pp.873-900. ⟨10.1007/s10579-021-09533-9⟩ (2021)
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Not all arguments are processed equally: a distributional model of argument complexity
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In: Springer Netherlands (2021)
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Abstract:
This work addresses some questions about language processing: what does it mean that natural language sentences are semantically complex? What semantic features can determine different degrees of difficulty for human comprehenders? Our goal is to introduce a framework for argument semantic complexity, in which the processing difficulty depends on the typicality of the arguments in the sentence, that is, their degree of compatibility with the selectional constraints of the predicate. We postulate that complexity depends on the difficulty of building a semantic representation of the event or the situation conveyed by a sentence. This representation can be either retrieved directly from the semantic memory or built dynamically by solving the constraints included in the stored representations. To support this postulation, we built a Distributional Semantic Model to compute a compositional cost function for the sentence unification process. Our evaluation on psycholinguistic datasets reveals that the model is able to account for semantic phenomena such as the context-sensitive update of argument expectations and the processing of logical metonymies.
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URL: https://hdl.handle.net/1721.1/132963
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Decoding Word Embeddings with Brain-Based Semantic Features ...
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Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge ...
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A comparative evaluation and analysis of three generations of Distributional Semantic Models ...
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Constructional associations trump lexical associations in processing valency coercion
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Common-Sense and Common-Knowledge. How much do Neural Language Models know about the world?
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In: http://etd.adm.unipi.it/theses/available/etd-03122021-000321/ (2021)
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I neologismi nelle edizioni del 2010 e del 2021 del dizionario "Zingarelli della lingua italiana"
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In: http://etd.adm.unipi.it/theses/available/etd-05102021-214231/ (2021)
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Large-scale Cross-lingual Word Sense Disambiguation using Parallel Corpora
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In: http://etd.adm.unipi.it/theses/available/etd-09112021-110903/ (2021)
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Probing the linguistic knowledge of word embeddings: A case study on colexification
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In: http://etd.adm.unipi.it/theses/available/etd-06212021-172428/ (2021)
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"Love is an open door but not a table". Come uomini e macchine 'comprendono' le metafore lessicalizzate e creative.
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In: http://etd.adm.unipi.it/theses/available/etd-03242021-214055/ (2021)
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Le interpretazioni del concetto di composizionalita' delle espressioni idiomatiche nella letteratura psicolinguistica
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In: http://etd.adm.unipi.it/theses/available/etd-09132021-151853/ (2021)
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