Here we will present work based on a corpus specially designed and elicited in order to provide data for the study of Classifier function in Greek Sign Language (GSL). Data elicitation was based on presentation to informants of a series of stimuli which lead to utterances entailing the set of Classifier functions met in the language. The whole set of video recorded data were annotated in order to provide an appropriate corpus for the investigation of Classifier instantiations. Annotation work was complemented by the use of a search tool external to the ELAN environment, which was developed in order to handle the whole of annotated material. This search tool allows to create a data base of annotated video clips, by exploiting the set of classification features used to annotate the video recorded data. Among the attribute-value pairs forming the complete set of annotation features used, the following tiers of annotation were adopted: a) "Discourse Unit", indicating the sentence or utterance in which a classifier is met, b) "CP____" for marking the maximal classifier predicate, c) "CP_GLOSS" to describe the semantic content of classifiers, and d) "HS" with font symbols as values for specifying the handshape or handshapes involved in signing. These tiers provide the necessary information to group pieces of data as to the different classifiers and classifier functions met in GSL, i.e. [Discourse Unit: various types of tables], [CP_MAX: round tables of different sizes], [CP_GLOSS: ROUND, FLAT, SIZE], [HS: D, L, B...]. Theoretical analysis of the so created linguistic data supports formulation of a proposal for Classifier behaviour which differentiates among three distinguished major grammar functions. The key property that allows for a principled account of Classifier behaviour is that Classifiers are semantic markers which create semantic classes of objects recognised to share a set of common semantic features. In this line, we will argue that Classifiers are morphemes articulated according to SL phonology primes. According to our proposal GSL utilises Classifier morphemes in three distinct ways:
To create new lexicon items: Classifier affixation adds specific semantic properties to an entity, making it part of the semantic class this specific Classifier identifies.
To add qualitative/quantitative values: Classifiers function as modifiers adding qualitative/quantitative values to syntactic heads or maximal phrases.
To serve co-indexing: In sign utterances, Classifiers may be used as pronominal elements, where co-indexing obligatorily involves an expanded set of agreement features which, apart from the standard features "Number" and "Gender", also includes the feature "Semantic Class".
@inproceedings{efthimiou:10005:sign-lang:lrec,
author = {Efthimiou, Eleni and Fotinea, Stavroula-Evita and Dimou, Athanasia-Lida and Kalimeris, Constandinos},
title = {Towards decoding Classifier function in {GSL}},
pages = {76--79},
editor = {Dreuw, Philippe and Efthimiou, Eleni and Hanke, Thomas and Johnston, Trevor and Mart{\'i}nez Ruiz, Gregorio and Schembri, Adam},
booktitle = {Proceedings of the {LREC2010} 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies},
maintitle = {7th International Conference on Language Resources and Evaluation ({LREC} 2010)},
publisher = {{European Language Resources Association (ELRA)}},
address = {Valletta, Malta},
day = {22--23},
month = may,
year = {2010},
language = {english},
url = {https://www.sign-lang.uni-hamburg.de/lrec/pub/10005.pdf}
}
| Fotinea, Stavroula-Evita