Visualizing deep-syntactic parser output

Data de publicació

2016-12-05T08:36:11Z

2016-12-05T08:36:11Z

2015

Resum

Comunicació presentada a la 2015 Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015), celebrada del 31 de maig al 5 de juny 2015 a Denver (CO, EUA).


“Deep-syntactic” dependency structures bridge the gap between the surface-syntactic structures as produced by state-of-the-art dependency parsers and semantic logical forms in that they abstract away from surfacesyntactic idiosyncrasies, but still keep the linguistic structure of a sentence. They have thus a great potential for such downstream applications as machine translation and summarization. In this demo paper, we propose an online version of a deep-syntactic parser that outputs deep-syntactic structures from plain sentences and visualizes them using the Brat tool. Along with the deep syntactic structures, the user can also inspect the visual presentation of the surface-syntactic structures that serve as input to the deep-syntactic parser and that are produced by the joint tagger and syntactic transition-based parser ran in the pipeline before deep-syntactic parsing takes place.


This work has been partially funded by the European Union’s Seventh Framework and Horizon 2020 Research and Innovation Programmes under the Grant Agreement numbers FP7-ICT-610411, FP7-SME- 606163, and H2020-RIA-645012.

Tipus de document

Objecte de conferència


Versió publicada

Llengua

Anglès

Publicat per

ACL (Association for Computational Linguistics)

Documents relacionats

Mihalcea R, Chai J, Anoop S, editors. Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies; 2015 May 31 - June 5; Denver, Colorado, United States. [Stroudsburg]: ACL; 2015. p. 56-60.

info:eu-repo/grantAgreement/EC/FP7/610411

info:eu-repo/grantAgreement/EC/FP7/606163

info:eu-repo/grantAgreement/EC/H2020/645012

Citació recomanada

Aquesta citació s'ha generat automàticament.

Drets

© ACL, Creative Commons Attribution 4.0 License

http://creativecommons.org/licenses/by/4.0/

Aquest element apareix en la col·lecció o col·leccions següent(s)