Integrating Paraphrasing into the FRANK QA System

Nick Ferguson; Liane Guillou; Kwabena Nuamah; Alan Bundy

Integrating Paraphrasing into the FRANK QA System

Nick Ferguson, Liane Guillou, Kwabena Nuamah, Alan Bundy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a study into the ability of paraphrase generation to increase the variety of natural language queries that the Frank Query Answering system can answer. We choose an English-French backtranslation model to generate paraphrases, which we test using a small challenge dataset. We conclude that this method is not useful for improving the variety of natural language queries that Frank can answer. Based on our observations, we recommend future work in the following directions: (1) allowing the ability to specify a form to paraphrase an input into; (2) constrained paraphrasing to avoid loss of information about query intent; and (3) the need for an automatic evaluation metric which captures semantic similarity, allows syntactic variation, and rewards preservation of query intent.

Original language	English
Title of host publication	Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022)
Editors	Alan Bundy, Denis Mareschal
Publisher	CEUR Workshop Proceedings (CEUR-WS.org)
Pages	29-34
Number of pages	6
Volume	3227
Publication status	Published - 2 Oct 2022
Event	The 3rd International Workshop on Human-Like Computing 2022 - Windsor, United Kingdom Duration: 28 Sep 2022 → 30 Sep 2022 Conference number: 3 https://ijclr22.doc.ic.ac.uk/hlc2022.html/index.html

Publication series

Name	Human-Like Computing Workshop 2022
Publisher	CEUR Workshop Proceedings
Volume	3227
ISSN (Electronic)	1613-0073

Workshop

Workshop	The 3rd International Workshop on Human-Like Computing 2022
Abbreviated title	HLC 2022
Country/Territory	United Kingdom
City	Windsor
Period	28/09/22 → 30/09/22
Internet address	https://ijclr22.doc.ic.ac.uk/hlc2022.html/index.html

Keywords

Question Answering
Paraphrasing
Backtranslation

Access to Document

Integrating Paraphrasing_FERGUSON_DOA15072022_VOR_CC-BYFinal published version, 804 KBLicence: Creative Commons: Attribution (CC-BY)

http://ceur-ws.org/Vol-3227/Furgeson-et-al.PP6.pdfLicence: Creative Commons: Attribution (CC-BY)

The 3rd International Workshop on Human-Like Computing 2022 (Event)
Alan Bundy (Editor) & Denis Mareschal (Editor)
28 Sep 2022 → 30 Sep 2022
Activity: Publication peer-review and editorial work types › Editorial activity

Cite this

Ferguson, N., Guillou, L., Nuamah, K., & Bundy, A. (2022). Integrating Paraphrasing into the FRANK QA System. In A. Bundy, & D. Mareschal (Eds.), Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022) (Vol. 3227, pp. 29-34). (Human-Like Computing Workshop 2022; Vol. 3227). CEUR Workshop Proceedings (CEUR-WS.org). http://ceur-ws.org/Vol-3227/Furgeson-et-al.PP6.pdf

@inproceedings{08f785f68483487f97e7ec0418259f62,

title = "Integrating Paraphrasing into the FRANK QA System",

abstract = "We present a study into the ability of paraphrase generation to increase the variety of natural language queries that the Frank Query Answering system can answer. We choose an English-French backtranslation model to generate paraphrases, which we test using a small challenge dataset. We conclude that this method is not useful for improving the variety of natural language queries that Frank can answer. Based on our observations, we recommend future work in the following directions: (1) allowing the ability to specify a form to paraphrase an input into; (2) constrained paraphrasing to avoid loss of information about query intent; and (3) the need for an automatic evaluation metric which captures semantic similarity, allows syntactic variation, and rewards preservation of query intent.",

keywords = "Question Answering, Paraphrasing, Backtranslation",

author = "Nick Ferguson and Liane Guillou and Kwabena Nuamah and Alan Bundy",

year = "2022",

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language = "English",

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series = "Human-Like Computing Workshop 2022",

publisher = "CEUR Workshop Proceedings (CEUR-WS.org)",

pages = "29--34",

editor = "Alan Bundy and Denis Mareschal",

booktitle = "Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022)",

note = "The 3rd International Workshop on Human-Like Computing 2022, HLC 2022 ; Conference date: 28-09-2022 Through 30-09-2022",

url = "https://ijclr22.doc.ic.ac.uk/hlc2022.html/index.html",

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Ferguson, N, Guillou, L , Nuamah, K & Bundy, A 2022, Integrating Paraphrasing into the FRANK QA System. in A Bundy & D Mareschal (eds), Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022). vol. 3227, Human-Like Computing Workshop 2022, vol. 3227, CEUR Workshop Proceedings (CEUR-WS.org), pp. 29-34, The 3rd International Workshop on Human-Like Computing 2022, Windsor, United Kingdom, 28/09/22. <http://ceur-ws.org/Vol-3227/Furgeson-et-al.PP6.pdf>

Integrating Paraphrasing into the FRANK QA System. / Ferguson, Nick; Guillou, Liane ; Nuamah, Kwabena et al.

Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022). ed. / Alan Bundy; Denis Mareschal. Vol. 3227 CEUR Workshop Proceedings (CEUR-WS.org), 2022. p. 29-34 (Human-Like Computing Workshop 2022; Vol. 3227).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Integrating Paraphrasing into the FRANK QA System

AU - Ferguson, Nick

AU - Guillou, Liane

AU - Nuamah, Kwabena

AU - Bundy, Alan

N1 - Conference code: 3

PY - 2022/10/2

Y1 - 2022/10/2

N2 - We present a study into the ability of paraphrase generation to increase the variety of natural language queries that the Frank Query Answering system can answer. We choose an English-French backtranslation model to generate paraphrases, which we test using a small challenge dataset. We conclude that this method is not useful for improving the variety of natural language queries that Frank can answer. Based on our observations, we recommend future work in the following directions: (1) allowing the ability to specify a form to paraphrase an input into; (2) constrained paraphrasing to avoid loss of information about query intent; and (3) the need for an automatic evaluation metric which captures semantic similarity, allows syntactic variation, and rewards preservation of query intent.

AB - We present a study into the ability of paraphrase generation to increase the variety of natural language queries that the Frank Query Answering system can answer. We choose an English-French backtranslation model to generate paraphrases, which we test using a small challenge dataset. We conclude that this method is not useful for improving the variety of natural language queries that Frank can answer. Based on our observations, we recommend future work in the following directions: (1) allowing the ability to specify a form to paraphrase an input into; (2) constrained paraphrasing to avoid loss of information about query intent; and (3) the need for an automatic evaluation metric which captures semantic similarity, allows syntactic variation, and rewards preservation of query intent.

KW - Question Answering

KW - Paraphrasing

KW - Backtranslation

M3 - Conference contribution

VL - 3227

T3 - Human-Like Computing Workshop 2022

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BT - Proceedings of the 3rd Human-Like Computing Workshop (HLC 2022)

A2 - Bundy, Alan

A2 - Mareschal, Denis

PB - CEUR Workshop Proceedings (CEUR-WS.org)

T2 - The 3rd International Workshop on Human-Like Computing 2022

Y2 - 28 September 2022 through 30 September 2022

ER -

Integrating Paraphrasing into the FRANK QA System

Abstract

Publication series

Workshop

Keywords

Access to Document

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Activities

The 3rd International Workshop on Human-Like Computing 2022 (Event)

Cite this