http://www.wordspace.collocations.de/ 2026-04-04T16:43:36+00:00 http://www.wordspace.collocations.de/ http://www.wordspace.collocations.de/lib/tpl/monobook/images/favicon.ico text/html 2010-11-01T14:07:20+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:abstract_concrete_nouns_discrimination?rev=1288616840&do=diff Task 2b - Abstract/Concrete Noun Discrimination Introduction The contrast between abstract and concrete words plays a central role in human cognition. Behavioural and neuropsychological evidence suggests that abstract and concrete concepts might be represented, retrieved and processed differently in the human brain (Noppeney, U. and C. Price (2004), "Retrieval of abstract semantics", text/html 2010-11-01T14:07:20+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:comparison_with_speaker-generated_features?rev=1288616840&do=diff Task 3: Comparison with Speaker-Generated Properties Introduction From a cognitive point of view, there is little doubt that salient properties of a concept are an important part of its "meaning", and subjects show a remarkable degree of agreement in tasks that require enumerating the typical properties of a concept: a dog text/html 2010-11-01T14:07:20+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:concrete_noun_categorization?rev=1288616840&do=diff Task 2a - Concrete Noun Categorization Introduction The goal of the sub-task is to group concrete nouns into semantic categories. The [data set] consists of 44 concrete nouns, belonging to 6 semantic categories (four natural and two man-made). The nouns are included in the feature norms described in McRae et al. (2005) (cf. text/html 2010-11-01T14:07:20+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:concrete_nouns_categorization?rev=1288616840&do=diff Task 1.a - Concrete Noun Categorization Introduction The goal of the sub-task is to group concrete nouns into semantic categories. The [data set] consists of 44 concrete nouns, belonging to 6 semantic categories (four animates and two inanimates). The nouns are included in the feature norms described in McRae et al. (2005) (cf. text/html 2010-11-01T14:07:20+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:correlation_with_free_association_norms?rev=1288616840&do=diff Task 1: Correlation with free association norms Overview and main goals In psychology, free associations are the first words that come to the mind of a native speaker when he or she is presented with a stimulus word, presumably retrieved from associative memory. It is tempting to make a connection between such free associations and the statistical association patterns of words in the linguistic experience of speakers, including both first-order associations ( text/html 2010-11-01T14:07:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:start?rev=1288616841&do=diff Shared Tasks from the ESSLLI 2008 Workshop Task 1: Free Association It is tempting to make a connection between the statistical association patterns of words -- both first-order associations (collocations) and higher-order associations (word space) text/html 2010-11-01T14:07:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://www.wordspace.collocations.de/doku.php/data:esslli2008:verb_categorization?rev=1288616841&do=diff Task 2c - Verb Categorization Introduction The goal of the sub-task is to group verbs into semantic categories. The [data set] consists of 45 verbs, belonging to 9 semantic classes. The classification scheme is inspired by P. Vinson & G. Vigliocco (2007), “Semantic Feature Production Norms for a Large Set of Objects and Events”,