Refine
Year of publication
- 2015 (2) (remove)
Document Type
- Part of a Book (1)
- Conference Proceeding (1)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2) (remove)
Keywords
- Präfix (2) (remove)
This paper deals with the encoding of affectedness in Abui, a Papuan language of Indonesia. Abui is a head-marking language of the rare type where the verbs are marked for their undergoer arguments (So, O) formally split into several subtypes. This marking has been previously analyzed as a type of semantic alignment sensitive among others to affectedness. Affectedness is understood here as a scalar property delimiting the predicate (following Tenny 1987 and Beavers 2011). The paper explores the structure of the affectedness scale for Abui, comparing the functions and meaning of three types of person prefix paradigms. We show that verbs with similar meaning, encoding the same type of change (in Beavers’ terms) can differ in their entailments. We also show that there may be additional dimensions in which affectedness can be measured, such as affected agents, and that the interpretation of the degree on the affectedness scale interacts with instigator’s (source of force) status on the referential hierarchy. While human agents in some cases allow lower degrees of affectedness, the inanimate forces select the maximal degree reading. We conclude, that despite a considerable amount of fluidity of marking (Fedden et al. 2013, 2014), the shifts in degree of affectedness can be predicted as lowering of the degree stipulated for the predicate.
This paper aims to work toward a proper understanding of the role of preverbal ge- in Old English (henceforth OE) and its disappearance in the course of Middle English. This prefix is reminiscent of its cognates in Modern German and Dutch (also written ge-) in its distribution, but even a cursory examination of the details reveals it to be quite distinct, as we will see. The proper characterization of that distribution, and of its diachronic development, has proven to be extremely difficult. I have thus carried out a large-scale corpus study using the York-Toronto-Helsinki parsed corpus of Old English prose (Taylor et al. 2003) and the Penn-Helsinki parsed corpus of Middle English, 2nd ed. (Kroch & Taylor 1999). This paper will report the results of the first phase of the project, involving patterns in the data that could be identified primarily on the basis of automatic searches in the corpora.