Question and Answer Classification in Czech Question Answering
Benchmark Dataset

D 2019

Question and Answer Classification in Czech Question Answering Benchmark Dataset

MEDVEĎ, Marek, Aleš HORÁK and Daša KUŠNIRÁKOVÁ

Basic information

Original name

Question and Answer Classification in Czech Question Answering Benchmark Dataset

Authors

MEDVEĎ, Marek (703 Slovakia, guarantor, belonging to the institution), Aleš HORÁK (203 Czech Republic) and Daša KUŠNIRÁKOVÁ (703 Slovakia)

Edition

Prague, Czech Republic, Proceedings of the 11th International Conference on Agents and Artificial Intelligence, Volume 2, p. 701-706, 6 pp. 2019

Publisher

SCITEPRESS

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

RIV identification code

RIV/00216224:14330/19:00107362

Organization unit

Faculty of Informatics

ISBN

978-989-758-350-6

DOI

http://dx.doi.org/10.5220/0007396907010706

UT WoS

000671841000075

Keywords in English

Question Answering; Question Classification; Answer Classification; Czech; Simple Question Answering Database; SQAD

Abstract

V originále

In this paper, we introduce a new updated version of the Czech Question Answering database SQAD v2.1 (Simple Question Answering Database) with the update being devoted to improved question and answer classification. The SQAD v2.1 database contains more than 8,500 question-answer pairs with all appropriate metadata for QA training and evaluation. We present the details and changes in the database structure as well as a new algorithm for detecting the question type and the actual answer type from the text of the question. The algorithm is evaluated with more than 4,000 question answer pairs reaching the F1-measure of 88% for question typed and 85% for answer type detection.

Links

GA18-23891S, research and development project

Name: Hyperintensionální usuzování nad texty přirozeného jazyka

Investor: Czech Science Foundation

MUNI/A/1018/2018, interní kód MU

Name: Rozsáhlé výpočetní systémy: modely, aplikace a verifikace VIII.

Investor: Masaryk University, Category A

Citovat

MEDVEĎ, Marek, Aleš HORÁK and Daša KUŠNIRÁKOVÁ. Question and Answer Classification in Czech Question Answering Benchmark Dataset. Online. In Ana Rocha, Luc Steels, Jaap van den Herik. Proceedings of the 11th International Conference on Agents and Artificial Intelligence, Volume 2. Prague, Czech Republic: SCITEPRESS, 2019, p. 701-706. ISBN 978-989-758-350-6. Available from: https://dx.doi.org/10.5220/0007396907010706.

@inproceedings{1521838,
   author = {Medveď, Marek and Horák, Aleš and Kušniráková, Daša},
   address = {Prague, Czech Republic},
   booktitle = {Proceedings of the 11th International Conference on Agents and Artificial Intelligence, Volume 2},
   doi = {http://dx.doi.org/10.5220/0007396907010706},
   editor = {Ana Rocha, Luc Steels, Jaap van den Herik},
   keywords = {Question Answering; Question Classification; Answer Classification; Czech; Simple Question Answering Database; SQAD},
   howpublished = {elektronická verze "online"},
   language = {eng},
   location = {Prague, Czech Republic},
   isbn = {978-989-758-350-6},
   pages = {701-706},
   publisher = {SCITEPRESS},
   title = {Question and Answer Classification in Czech Question Answering Benchmark Dataset},
   year = {2019}
}

TY  - JOUR
ID  - 1521838
AU  - Medveď, Marek - Horák, Aleš - Kušniráková, Daša
PY  - 2019
TI  - Question and Answer Classification in Czech Question Answering Benchmark Dataset
PB  - SCITEPRESS
CY  - Prague, Czech Republic
SN  - 9789897583506
KW  - Question Answering
KW  - Question Classification
KW  - Answer Classification
KW  - Czech
KW  - Simple Question Answering Database
KW  - SQAD
N2  - In this paper, we introduce a new updated version of the Czech Question Answering database SQAD v2.1 (Simple Question Answering Database) with the update being devoted to improved question and answer classification. The SQAD v2.1 database contains more than 8,500 question-answer pairs with all appropriate metadata for QA training and evaluation. We present the details and changes in the database structure as well as a new algorithm for detecting the question type and the actual answer type from the text of the question. The algorithm is evaluated with more than 4,000 question answer pairs reaching the F1-measure of 88% for question typed and 85% for answer type detection.
ER  -

MEDVEĎ, Marek, Aleš HORÁK and Daša KUŠNIRÁKOVÁ. Question and Answer Classification in Czech Question Answering Benchmark Dataset. Online. In Ana Rocha, Luc Steels, Jaap van den Herik. \textit{Proceedings of the 11th International Conference on Agents and Artificial Intelligence, Volume 2}. Prague, Czech Republic: SCITEPRESS, 2019, p.~701-706. ISBN~978-989-758-350-6. Available from: https://dx.doi.org/10.5220/0007396907010706.

Detailed Information on Publication Record