In this paper, the authors challenge the widespread view that the distinction between endocentric and exocentric compounds is fundamentally semantic. On the basis of data from Greek and Cypriot they propose, instead, that this is a structural distinction and that semantics cannot be a safe criterion for classifying exocentric compounds into various categories. They show that morphological features, e.g. gender and inflection class, cannot define exocentricity, since both Greek and Cypriot have many endocentric compounds displaying different features from those of their head. It is suggested that exocentricity might be an epiphenomenon of the order of application of the word-formation processes, according to which, when compounding and derivation co-occur within the same morphologically complex item, compounding precedes derivation. In contrast, a structure is endocentric if it contains only compounding, or involves derivation and compounding, in this particular order. Finally, the authors provide evidence that exocentric compounds may belong to the productive word-formation mechanism. * A draft version of this paper has been presented at the 14th International Morphology Meeting (Budapest, May 13-16, 2010). We thank the scientific committee and the audience for their most constructive remarks. We are also grateful to Laurie Bauer and three anonymous reviewers for their precious comments. This work has been supported by the Carathéodory Programme (D.159) of the University of Patras.
One of the central problems in the semantics of derived words is polysemy (see, for example, the recent contributions by Lieber 2016 and Plag et al. 2018 ). In this paper, we tackle the problem of disambiguating newly derived words in context by applying Distributional Semantics ( Firth 1957 ) to deverbal -ment nominalizations (e.g. bedragglement, emplacement). We collected a dataset containing contexts of low frequency deverbal -ment nominalizations (55 types, 406 tokens, see Appendix B) extracted from large corpora such as the Corpus of Contemporary American English. We chose low frequency derivatives because high frequency formations are often lexicalized and thus tend to not exhibit the kind of polysemous readings we are interested in. Furthermore, disambiguating low-frequency words presents an especially difficult task because there is little to no prior knowledge about these words from which their semantic properties can be extrapolated. The data was manually annotated according to eventive vs. non-eventive interpretations, allowing also an ambiguous label in those cases where the context did not disambiguate. Our question then was to what extent, and under which conditions, context-derived representations such as those of Distributional Semantics can be successfully employed in the disambiguation of low-frequency derivatives. Our results show that, first, our models are able to distinguish between eventive and non-eventive readings with some success. Second, very small context windows are sufficient to find the intended interpretation in the majority of cases. Third, ambiguous instances tend to be classified as events. Fourth, the performance of the classifier differed for different subcategories of nouns, with non-eventive derivatives being harder to classify correctly. We present indirect evidence that this is due to the semantic similarity of abstract non-eventive nouns to eventive nouns. Overall, this paper demonstrates that distributional semantic models can be fruitfully employed for the disambiguation of low frequency words in spite of the scarcity of available contextual information. 1
In this contribution, I offer a summary of my 2014 Ph.D. dissertation from the University of Patras on headedness in word formation and lexical semantics.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.