TY - GEN

T1 - Natural Questions in Icelandic

AU - Snæbjarnarson, Vésteinn

AU - Einarsson, Hafsteinn

N1 - Funding Information: We would like to thank Akari Asai for granting us access to the annotation software we adapted for this project. We would also like to thank the student annotators: Bergur Tareq Tamimi, Ingibjörg Iða Auðunardóttir, Unnar Ingi Sæmundsson, Hildur Bjarnadóttir and Helgi Valur Gunnarsson. They were supported by a grant from the Icelandic student innovation fund. Finally, we thank the anonymous reviewers for their helpful comments and questions. Publisher Copyright: © European Language Resources Association (ELRA), licensed under CC-BY-NC-4.0.

PY - 2022

Y1 - 2022

N2 - We present the first extractive question answering (QA) dataset for Icelandic, Natural Questions in Icelandic (NQiI). Developing such datasets is important for the development and evaluation of Icelandic QA systems. It also aids in the development of QA methods that need to work for a wide range of morphologically and grammatically different languages in a multilingual setting. The dataset was created by asking contributors to come up with questions they would like to know the answer to. Later, they were tasked with finding answers to each others questions following a previously published methodology. The questions are Natural in the sense that they are real questions posed out of interest in knowing the answer. The complete dataset contains 18 thousand labeled entries of which 5,568 are directly suitable for training an extractive QA system for Icelandic. The dataset is a valuable resource for Icelandic which we demonstrate by creating and evaluating a system capable of extractive QA in Icelandic.

AB - We present the first extractive question answering (QA) dataset for Icelandic, Natural Questions in Icelandic (NQiI). Developing such datasets is important for the development and evaluation of Icelandic QA systems. It also aids in the development of QA methods that need to work for a wide range of morphologically and grammatically different languages in a multilingual setting. The dataset was created by asking contributors to come up with questions they would like to know the answer to. Later, they were tasked with finding answers to each others questions following a previously published methodology. The questions are Natural in the sense that they are real questions posed out of interest in knowing the answer. The complete dataset contains 18 thousand labeled entries of which 5,568 are directly suitable for training an extractive QA system for Icelandic. The dataset is a valuable resource for Icelandic which we demonstrate by creating and evaluating a system capable of extractive QA in Icelandic.

KW - Icelandic

KW - QA

KW - question answering

UR - http://www.scopus.com/inward/record.url?scp=85139102522&partnerID=8YFLogxK

M3 - Article in proceedings

AN - SCOPUS:85139102522

SP - 4488

EP - 4496

BT - 2022 Language Resources and Evaluation Conference, LREC 2022

A2 - Calzolari, Nicoletta

A2 - Bechet, Frederic

A2 - Blache, Philippe

A2 - Choukri, Khalid

A2 - Cieri, Christopher

A2 - Declerck, Thierry

A2 - Goggi, Sara

A2 - Isahara, Hitoshi

A2 - Maegaard, Bente

A2 - Mariani, Joseph

A2 - Mazo, Helene

A2 - Odijk, Jan

A2 - Piperidis, Stelios

PB - European Language Resources Association (ELRA)

T2 - 13th International Conference on Language Resources and Evaluation Conference, LREC 2022

Y2 - 20 June 2022 through 25 June 2022

ER -