Automatic Semantic Classification of German Preposition Types: Comparing Hard and Soft Clustering Approaches across Features
Maximilian Köper, Sabine Schulte im Walde
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (ACL), pp. 256–263, 2016.
Abstract
This paper addresses an automatic classification of preposition types in German, comparing hard and soft clustering approaches and various window- and syntax-based co-occurrence features. We show that (i) the semantically most salient preposition features (i.e., subcategorised nouns) are the most successful, and that (ii) soft clustering approaches are required for the task but reveal quite different attitudes towards predicting ambiguity.Links
doi: 10.18653/v1/P16-2042
BibTeX
@inproceedings{koeper16_acl,
title = {Automatic Semantic Classification of German Preposition Types: Comparing Hard and Soft Clustering Approaches across Features},
author = {Köper, Maximilian and {Schulte im Walde}, Sabine},
year = {2016},
booktitle = {Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (ACL)},
pages = {256–263},
doi = {10.18653/v1/P16-2042}
}