Please use this identifier to cite or link to this item:

http://hdl.handle.net/10609/61146
Title: Verb similarity : Comparing corpus and psycholinguistic data
Author: Gil-Vallejo, Lara
Coll-Florit, Marta  
Castellón Masalles, Irene
Turmo, Jordi
Keywords: linguistics
corpus linguistics
psycholinguistics
verb similarity
semantic roles
word associations
Issue Date: 26-Jan-2017
Publisher: Corpus Linguistics and Linguistic Theory - The Gruyter
Citation: Gil-Vallejo, L.; Coll-Florit, M.; Castellón, I.; Turmo, J. (2017). "Verb similarity: Comparing corpus and psycholinguistic data". Corpus Linguistics and Linguistic Theory. ISSN (Online) 1613-7035. DOI: 10.1515/cllt-2016-0045
Abstract: Similarity, which plays a key role in fields like cognitive science, psycholinguistics and natural language processing, is a broad and multifaceted concept. In this work we analyse how two approaches that belong to different perspectives, the corpus view and the psycholinguistic view, articulate similarity between verb senses in Spanish. Specifically, we compare the similarity between verb senses based on their argument structure, which is captured through semantic roles, with their similarity defined by word associations. We address the question of whether verb argument structure, which reflects the expression of the events, and word associations, which are related to the speakers' organization of the mental lexicon, shape similarity between verbs in a congruent manner, a topic which has not been explored previously. While we find significant correlations between verb sense similarities obtained from these two approaches, our findings also highlight some discrepancies between them and the importance of the degree of abstraction of the corpus annotation and psycholinguistic representations.
Language: English
URI: http://hdl.handle.net/10609/61146
ISSN: 1613-7035
Appears in Collections:Articles

Share:
Export:
Files in This Item:
File Description SizeFormat 
Gil-Vallejo et al_2017_Corpus Linguistics and Linguistic Theory_preprint.pdf970.02 kBAdobe PDFView/Open

This item is licensed under a Creative Commons License Creative Commons