Composition of Word Representations Improves Semantic Role Labelling

Anthology ID:: D14-1045
Volume:: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Month:: October
Year:: 2014
Address:: Doha, Qatar
Editors:: Alessandro Moschitti, Bo Pang, Walter Daelemans
Venue:: EMNLP
SIG:: SIGDAT
Publisher:: Association for Computational Linguistics
Note:
Pages:: 407–413
Language:
URL:: https://aclanthology.org/D14-1045
DOI:: 10.3115/v1/D14-1045
Bibkey:
Cite (ACL):: Michael Roth and Kristian Woodsend. 2014. Composition of Word Representations Improves Semantic Role Labelling. In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 407–413, Doha, Qatar. Association for Computational Linguistics.
Cite (Informal):: Composition of Word Representations Improves Semantic Role Labelling (Roth & Woodsend, EMNLP 2014)
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PDF:: https://preview.aclanthology.org/improve-issue-templates/D14-1045.pdf