QRGS – Question Responses Generation via crowdsourcing

QRGS stands for the Question Responses Generation System. It is an online game-like framework designed for gathering various types of question responses. A QRGS user is asked to read a simple story and impersonate its main character. As the story unfolds the user is confronted with four questions and (s)he is expected to answer these in the way the main character would. In this way, we obtain responses to questions of a desired type. The data gathered via QRGS is a useful supplement to the linguistic data already present in language corpora – especially for languages for which such resources are sparse. As such, it opens the possibility for better understanding of the use of questions in natural language dialogues and analysing the response space of such questions. In this paper, we present the main idea of QRGS and the results of five studies (in Polish and in English) that test the framework. Our discussion addresses issues concerning the efficiency and accuracy of the proposed approach. We also discuss the availability of the QRGS and its potential future improvements.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-09-01
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
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article

QRGS – Question Responses Generation via crowdsourcing

SHILAP Revista de lepidopterología
Quantum Information and Cryptography
article

QRGS – Question Responses Generation via crowdsourcing

article en

Abstract

QRGS stands for the Question Responses Generation System. It is an online game-like framework designed for gathering various types of question responses. A QRGS user is asked to read a simple story and impersonate its main character. As the story unfolds the user is confronted with four questions and (s)he is expected to answer these in the way the main character would. In this way, we obtain responses to questions of a desired type. The data gathered via QRGS is a useful supplement to the linguistic data already present in language corpora – especially for languages for which such resources are sparse. As such, it opens the possibility for better understanding of the use of questions in natural language dialogues and analysing the response space of such questions. In this paper, we present the main idea of QRGS and the results of five studies (in Polish and in English) that test the framework. Our discussion addresses issues concerning the efficiency and accuracy of the proposed approach. We also discuss the availability of the QRGS and its potential future improvements.

SHILAP Revista de lepidopterología
Quality Education
Openalex Percentile: Top 54%
Quantum Information and Cryptography
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