Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions

Andrew D. Walker; Panos Alexopoulos; Andrew Starkey; Jeff Z. Pan; José Manuel Gómez-Pérez; Advaith Siddharthan

doi:10.1007/978-3-319-31676-5_17

Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions

Andrew D. Walker^*, Panos Alexopoulos, Andrew Starkey, Jeff Z. Pan, José Manuel Gómez-Pérez, Advaith Siddharthan

^*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Question Answering research has long recognised that the identification of the type of answer being requested is a fundamental step in the interpretation of a question as a whole. Previous strategies have ranged from trivial keyword matches, to statistical analyses, to well-defined algorithms based on shallow syntactic parses with userinteraction for ambiguity resolution. A novel strategy combining deep NLP on both syntactic and dependency parses with supervised learning is introduced and results that improve on extant alternatives reported. The impact of the strategy on QALD is also evaluated with a proprietary Question Answering system and its positive results analysed.

Original language	English
Title of host publication	Semantic Technology
Subtitle of host publication	5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers
Editors	Guilin Qi, Kouji Kozaki, Jeff Z Pan, Siwei Yu
Publisher	Springer-Verlag
Pages	235-251
Number of pages	17
Volume	9544
ISBN (Electronic)	978-3-319-31676-5
ISBN (Print)	978-3-319-31675-8
DOIs	https://doi.org/10.1007/978-3-319-31676-5_17
Publication status	Published - 2016
Event	5th Joint International Conference on Semantic Technology, JIST 2015 - Yichang, China Duration: 11 Nov 2015 → 13 Nov 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9544
ISSN (Print)	03029743
ISSN (Electronic)	16113349

Conference

Conference	5th Joint International Conference on Semantic Technology, JIST 2015
Country	China
City	Yichang
Period	11/11/15 → 13/11/15

Access to Document

10.1007/978-3-319-31676-5_17Licence: Unspecified

Link to publication in Scopus

Fingerprint Dive into the research topics of 'Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions'. Together they form a unique fingerprint.

Profiles

Andrew Starkey

Engineering, Engineering - Senior Lecturer
Engineering (Research Theme)
Centre for Applied Dynamics Research (CADR)

Person: Academic

Cite this

Walker, A. D., Alexopoulos, P., Starkey, A., Pan, J. Z., Gómez-Pérez, J. M., & Siddharthan, A. (2016). Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions. In G. Qi, K. Kozaki, J. Z. Pan, & S. Yu (Eds.), Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers (Vol. 9544, pp. 235-251). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9544). Springer-Verlag. https://doi.org/10.1007/978-3-319-31676-5_17

Answer type identification for question answering : Supervised learning of dependency graph patterns from natural language questions. / Walker, Andrew D.; Alexopoulos, Panos; Starkey, Andrew ; Pan, Jeff Z.; Gómez-Pérez, José Manuel; Siddharthan, Advaith.

Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers. ed. / Guilin Qi; Kouji Kozaki; Jeff Z Pan; Siwei Yu. Vol. 9544 Springer-Verlag, 2016. p. 235-251 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9544).

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

Walker, AD, Alexopoulos, P, Starkey, A , Pan, JZ, Gómez-Pérez, JM & Siddharthan, A 2016, Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions. in G Qi, K Kozaki, JZ Pan & S Yu (eds), Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers. vol. 9544, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9544, Springer-Verlag, pp. 235-251, 5th Joint International Conference on Semantic Technology, JIST 2015, Yichang, China, 11/11/15. https://doi.org/10.1007/978-3-319-31676-5_17

Walker AD, Alexopoulos P, Starkey A , Pan JZ, Gómez-Pérez JM, Siddharthan A. Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions. In Qi G, Kozaki K, Pan JZ, Yu S, editors, Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers. Vol. 9544. Springer-Verlag. 2016. p. 235-251. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-31676-5_17

Walker, Andrew D. ; Alexopoulos, Panos ; Starkey, Andrew ; Pan, Jeff Z. ; Gómez-Pérez, José Manuel ; Siddharthan, Advaith. / Answer type identification for question answering : Supervised learning of dependency graph patterns from natural language questions. Semantic Technology: 5th Joint International Conference, JIST 2015, Yichang, China, November 11-13, 2015, Revised Selected Papers. editor / Guilin Qi ; Kouji Kozaki ; Jeff Z Pan ; Siwei Yu. Vol. 9544 Springer-Verlag, 2016. pp. 235-251 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{5f31c5574bb24521aea610a1e5c88471,

title = "Answer type identification for question answering: Supervised learning of dependency graph patterns from natural language questions",

abstract = "Question Answering research has long recognised that the identification of the type of answer being requested is a fundamental step in the interpretation of a question as a whole. Previous strategies have ranged from trivial keyword matches, to statistical analyses, to well-defined algorithms based on shallow syntactic parses with userinteraction for ambiguity resolution. A novel strategy combining deep NLP on both syntactic and dependency parses with supervised learning is introduced and results that improve on extant alternatives reported. The impact of the strategy on QALD is also evaluated with a proprietary Question Answering system and its positive results analysed.",

author = "Walker, {Andrew D.} and Panos Alexopoulos and Andrew Starkey and Pan, {Jeff Z.} and G{\'o}mez-P{\'e}rez, {Jos{\'e} Manuel} and Advaith Siddharthan",

note = "Acknowledgement This research has been partly funded by the European Commission within the 7th Framework Programme/Marie Curie Industry-Academia Partnerships and Pathways schema/PEOPLE Work Programme 2011 project K-Drive number 286348 (cf. http://www.kdrive-project.eu).; 5th Joint International Conference on Semantic Technology, JIST 2015 ; Conference date: 11-11-2015 Through 13-11-2015",

year = "2016",

doi = "10.1007/978-3-319-31676-5_17",

language = "English",

isbn = "978-3-319-31675-8",

volume = "9544",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer-Verlag",

pages = "235--251",

editor = "Qi, {Guilin } and Kouji Kozaki and Pan, {Jeff Z} and Siwei Yu",

booktitle = "Semantic Technology",

}

TY - GEN

T1 - Answer type identification for question answering

T2 - 5th Joint International Conference on Semantic Technology, JIST 2015

AU - Walker, Andrew D.

AU - Alexopoulos, Panos

AU - Starkey, Andrew

AU - Pan, Jeff Z.

AU - Gómez-Pérez, José Manuel

AU - Siddharthan, Advaith

N1 - Acknowledgement This research has been partly funded by the European Commission within the 7th Framework Programme/Marie Curie Industry-Academia Partnerships and Pathways schema/PEOPLE Work Programme 2011 project K-Drive number 286348 (cf. http://www.kdrive-project.eu).

PY - 2016

Y1 - 2016

N2 - Question Answering research has long recognised that the identification of the type of answer being requested is a fundamental step in the interpretation of a question as a whole. Previous strategies have ranged from trivial keyword matches, to statistical analyses, to well-defined algorithms based on shallow syntactic parses with userinteraction for ambiguity resolution. A novel strategy combining deep NLP on both syntactic and dependency parses with supervised learning is introduced and results that improve on extant alternatives reported. The impact of the strategy on QALD is also evaluated with a proprietary Question Answering system and its positive results analysed.

AB - Question Answering research has long recognised that the identification of the type of answer being requested is a fundamental step in the interpretation of a question as a whole. Previous strategies have ranged from trivial keyword matches, to statistical analyses, to well-defined algorithms based on shallow syntactic parses with userinteraction for ambiguity resolution. A novel strategy combining deep NLP on both syntactic and dependency parses with supervised learning is introduced and results that improve on extant alternatives reported. The impact of the strategy on QALD is also evaluated with a proprietary Question Answering system and its positive results analysed.

UR - http://www.scopus.com/inward/record.url?scp=84961675218&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-31676-5_17

DO - 10.1007/978-3-319-31676-5_17

M3 - Conference contribution

AN - SCOPUS:84961675218

SN - 978-3-319-31675-8

VL - 9544

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 235

EP - 251

BT - Semantic Technology

A2 - Qi, Guilin

A2 - Kozaki, Kouji

A2 - Pan, Jeff Z

A2 - Yu, Siwei

PB - Springer-Verlag

Y2 - 11 November 2015 through 13 November 2015

ER -