Towards Czech Answer Type Analysis

D 2018

Towards Czech Answer Type Analysis

KUŠNIRÁKOVÁ, Daša a Marek MEDVEĎ

Základní údaje

Originální název

Towards Czech Answer Type Analysis

Autoři

KUŠNIRÁKOVÁ, Daša a Marek MEDVEĎ

Vydání

Brno, Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018, od s. 41-51, 11 s. 2018

Nakladatel

Tribun EU

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10200 1.2 Computer and information sciences

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

URL

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14330/18:00101540

Organizační jednotka

Fakulta informatiky

ISBN

978-80-263-1517-9

ISSN

UT WoS

000612420300006

EID Scopus

2-s2.0-85062200961

Klíčová slova anglicky

question answering; question classification; answer classifica-tion; Czech; Simple Question Answering Database; SQAD

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 16. 5. 2022 15:40, Mgr. Michal Petr

Anotace

V originále

In this paper, we introduce two answer type detection systems for Czech language. Based on the input question, the goal of these tools is to recognise the question type and extract an appropriate answer type. Except for the same goal, these systems are completely different. The first one is a rule based system utilising Czech Wordnet for hypernym detection. The second one uses a machine learning approach in form of a neural network. We present architectures of these two systems and offer a detailed evaluation on more than 8,500 question-answer pairs using the SQAD v2.1 benchmark dataset.

Návaznosti

GA18-23891S, projekt VaV

Název: Hyperintensionální usuzování nad texty přirozeného jazyka

Investor: Grantová agentura ČR, Hyperintensionální usuzování nad texty přirozeného jazyka

Citovat

KUŠNIRÁKOVÁ, Daša a Marek MEDVEĎ. Towards Czech Answer Type Analysis. In Aleš Horák, Pavel Rychlý and Adam Rambousek. Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018. Brno: Tribun EU, 2018, s. 41-51. ISBN 978-80-263-1517-9.

@inproceedings{1484738,
   author = {Kušniráková, Daša and Medveď, Marek},
   address = {Brno},
   booktitle = {Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018},
   editor = {Aleš Horák, Pavel Rychlý and Adam Rambousek},
   keywords = {question answering; question classification; answer classifica-tion; Czech; Simple Question Answering Database; SQAD},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Brno},
   isbn = {978-80-263-1517-9},
   pages = {41-51},
   publisher = {Tribun EU},
   title = {Towards Czech Answer Type Analysis},
   url = {https://nlp.fi.muni.cz/raslan/2018/paper13-Kusnirakova_Medved.pdf},
   year = {2018}
}

TY  - CONF
ID  - 1484738
AU  - Kušniráková, Daša - Medveď, Marek
PY  - 2018
TI  - Towards Czech Answer Type Analysis
PB  - Tribun EU
CY  - Brno
SN  - 9788026315179
KW  - question answering
KW  - question classification
KW  - answer classifica-tion
KW  - Czech
KW  - Simple Question Answering Database
KW  - SQAD
UR  - https://nlp.fi.muni.cz/raslan/2018/paper13-Kusnirakova_Medved.pdf
N2  - In this paper, we introduce two answer type detection systems for Czech language. Based on the input question, the goal of these tools is to recognise the question type and extract an appropriate answer type. Except for the same goal, these systems are completely different. The first one is a rule based system utilising Czech Wordnet for hypernym detection. The second one uses a machine learning approach in form of a neural network. We present architectures of these two systems and offer a detailed evaluation on more than 8,500 question-answer pairs using the SQAD v2.1 benchmark dataset.
ER  -

KUŠNIRÁKOVÁ, Daša a Marek MEDVEĎ. Towards Czech Answer Type Analysis. In Aleš Horák, Pavel Rychlý and Adam Rambousek. \textit{Proceedings of the Twelfth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2018}. Brno: Tribun EU, 2018, s.~41-51. ISBN~978-80-263-1517-9.

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