Characterizing Response Types And Revealing Noun Ambiguity In German Association Norms
نویسندگان
چکیده
This paper presents an analysis of semantic association norms for German nouns. In contrast to prior studies, we not only collected associations elicited by written representations of target objects but also by their pictorial representations. In a first analysis, we identified systematic differences in the type and distribution of associate responses for the two presentation forms. In a second analysis, we applied a soft cluster analysis to the collected targetresponse pairs. We subsequently used the clustering to predict noun ambiguity and to discriminate senses in our target nouns.
منابع مشابه
Association Norms of German Noun Compounds
This paper introduces association norms of German noun compounds as a lexical-semantic resource for cognitive and computational linguistics research on compositionality. Based on an existing database of German noun compounds, we collected human associations to the compounds and their constituents within a web experiment. The current study describes the collection process and a part-of-speech an...
متن کاملAssociation norms for German noun compounds and their constituents.
We present a collection of association norms for 246 German depictable compound nouns and their constituents, comprising 58,652 association tokens distributed over 26,004 stimulus-associate pair types. Analyses of the data revealed that participants mainly provided noun associates, followed by adjective and verb associates. In corpus analyses, co-occurrence values for compounds and their associ...
متن کاملFeature Norms of German Noun Compounds
This paper presents a new data collection of feature norms for 572 German nounnoun compounds. The feature norms complement existing data sets for the same targets, including compositionality ratings, association norms, and images. We demonstrate that the feature norms are potentially useful for research on the nounnoun compounds and their semantic transparency: The feature overlap of the compou...
متن کاملThe Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective
In this paper, we explore the role of constituent properties in English and German noun-noun compounds (corpus frequencies of the compounds and their constituents; productivity and ambiguity of the constituents; and semantic relations between the constituents), when predicting the degrees of compositionality of the compounds within a vector space model. The results demonstrate that the empirica...
متن کاملUsing Web Corpora for the Automatic Acquisition of Lexical-Semantic Knowledge
This article presents two case studies to explore whether and how web corpora can be used to automatically acquire lexical-semantic knowledge from distributional information. For this purpose, we compare three German web corpora and a traditional newspaper corpus on modelling two types of semantic relatedness: (1) Assuming that free word associations are semantically related to their stimuli, w...
متن کامل