Ellipsis resolution as question answering: An evaluation

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

Ellipsis resolution as question answering : An evaluation. / Aralikatte, Rahul; Lamm, Matthew; Hardt, Daniel; Søgaard, Anders.

EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, 2021. p. 810-817.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Aralikatte, R, Lamm, M, Hardt, D & Søgaard, A 2021, Ellipsis resolution as question answering: An evaluation. in EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, pp. 810-817, 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021, Virtual, Online, 19/04/2021. https://doi.org/10.18653/v1/2021.eacl-main.68

APA

Aralikatte, R., Lamm, M., Hardt, D., & Søgaard, A. (2021). Ellipsis resolution as question answering: An evaluation. In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference (pp. 810-817). Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.eacl-main.68

Vancouver

Aralikatte R, Lamm M, Hardt D, Søgaard A. Ellipsis resolution as question answering: An evaluation. In EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics. 2021. p. 810-817 https://doi.org/10.18653/v1/2021.eacl-main.68

Author

Aralikatte, Rahul ; Lamm, Matthew ; Hardt, Daniel ; Søgaard, Anders. / Ellipsis resolution as question answering : An evaluation. EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference. Association for Computational Linguistics, 2021. pp. 810-817

Bibtex

@inproceedings{41c83466b8794e808585fa8aee65f07c,
title = "Ellipsis resolution as question answering: An evaluation",
abstract = "Most, if not all forms of ellipsis (e.g., 'so does Mary') are similar to reading comprehension questions ('what does Mary do'), in that in order to resolve them, we need to identify an appropriate text span in the preceding discourse. Following this observation, we present an alternative approach for English ellipsis resolution relying on architectures developed for question answering (QA). We present both single-task models, and joint models trained on auxiliary QA and coreference resolution datasets, clearly outperforming the current state of the art for Sluice Ellipsis (from 70.00 to 86.01 F1) and Verb Phrase Ellipsis (from 72.89 to 78.66 F1).",
author = "Rahul Aralikatte and Matthew Lamm and Daniel Hardt and Anders S{\o}gaard",
year = "2021",
doi = "10.18653/v1/2021.eacl-main.68",
language = "English",
pages = "810--817",
booktitle = "EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference",
publisher = "Association for Computational Linguistics",
note = "16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021 ; Conference date: 19-04-2021 Through 23-04-2021",

}

RIS

TY - GEN

T1 - Ellipsis resolution as question answering

T2 - 16th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2021

AU - Aralikatte, Rahul

AU - Lamm, Matthew

AU - Hardt, Daniel

AU - Søgaard, Anders

PY - 2021

Y1 - 2021

N2 - Most, if not all forms of ellipsis (e.g., 'so does Mary') are similar to reading comprehension questions ('what does Mary do'), in that in order to resolve them, we need to identify an appropriate text span in the preceding discourse. Following this observation, we present an alternative approach for English ellipsis resolution relying on architectures developed for question answering (QA). We present both single-task models, and joint models trained on auxiliary QA and coreference resolution datasets, clearly outperforming the current state of the art for Sluice Ellipsis (from 70.00 to 86.01 F1) and Verb Phrase Ellipsis (from 72.89 to 78.66 F1).

AB - Most, if not all forms of ellipsis (e.g., 'so does Mary') are similar to reading comprehension questions ('what does Mary do'), in that in order to resolve them, we need to identify an appropriate text span in the preceding discourse. Following this observation, we present an alternative approach for English ellipsis resolution relying on architectures developed for question answering (QA). We present both single-task models, and joint models trained on auxiliary QA and coreference resolution datasets, clearly outperforming the current state of the art for Sluice Ellipsis (from 70.00 to 86.01 F1) and Verb Phrase Ellipsis (from 72.89 to 78.66 F1).

UR - http://www.scopus.com/inward/record.url?scp=85107308576&partnerID=8YFLogxK

U2 - 10.18653/v1/2021.eacl-main.68

DO - 10.18653/v1/2021.eacl-main.68

M3 - Article in proceedings

AN - SCOPUS:85107308576

SP - 810

EP - 817

BT - EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference

PB - Association for Computational Linguistics

Y2 - 19 April 2021 through 23 April 2021

ER -

ID: 287066069