Previous approaches to multilingual semantic dependency parsing treat languages independently, without exploiting the similarities between semantic structures across languages. We experiment with a new approach where we combine resources from a pair of languages in the CoNLL 2009 shared task (Hajič et al., 2009) to build a polyglot semantic role la-beler. Notwithstanding the absence of parallel data, and the dissimilarity in annotations between languages, our approach results in an improvement in SRL performance on multiple languages over a monolingual baseline. Analysis of the polyglot model shows it to be advantageous in lower-resource settings.
CITATION STYLE
Mulcaire, P., Swayamdipta, S., & Smith, N. A. (2018). Polyglot semantic role labeling. In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) (Vol. 2, pp. 667–672). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p18-2106
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