@inproceedings{L16-1448,
 abstract = {We propose a novel method for detecting optional arguments of Hungarian verbs using only positive data. We introduce a custom variant of collexeme analysis that explicitly models the noise in verb frames. Our method is, for the most part, unsupervised: we use the spectral clustering algorithm described in Brew and Schulte in Walde (2002) to build a noise model from a short, manually verified seed list of verbs. We experimented with both raw count- and context-based clusterings and found their performance almost identical. The code for our algorithm and the frame list are freely available at http://hlt.bme.hu/en/resources/tade.
},
 address = {Portorož, Slovenia},
 author = {Andras Kornai and Dávid Márk Nemeskey and Gábor Recski},
 booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)},
 month = {May},
 pages = {2815--2818},
 publisher = {European Language Resources Association (ELRA)},
 title = {Detecting Optional Arguments of Verbs},
 url = {https://www.aclweb.org/anthology/L16-1448},
 year = {2016}
}