@inproceedings{ahrendt-demberg:2016:N16-1,
title = {Improving event prediction by representing script participants},
author = {Simon Ahrendt and Vera Demberg},
url = {http://www.aclweb.org/anthology/N16-1067},
year = {2016},
date = {2016-06-01},
booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
pages = {546-551},
publisher = {Association for Computational Linguistics},
address = {San Diego, California},
abstract = {Automatically learning script knowledge has proved difficult, with previous work not or just barely beating a most-frequent baseline. Script knowledge is a type of world knowledge which can however be useful for various task in NLP and psycholinguistic modelling. We here propose a model that includes participant information (i.e., knowledge about which participants are relevant for a script) and show, on the Dinners from Hell corpus as well as the InScript corpus, that this knowledge helps us to significantly improve prediction performance on the narrative cloze task.},
pubstate = {published},
type = {inproceedings}
}