INST: L_042Question answering (QA) task intends to answer questions posed by humans in natural language. However, the QA task was not investigated for the Azerbaijani language due to the lack of a dataset. In this study, we introduce AzQuAD: Azerbaijani Question Answering Dataset that contains 5000 question-answer pairs based on Azerbaijani Wikipedia articles. We also experimented the performance of prominent QA and pre-trained models on the AzQuAD
Question answering is a subfield of information retrieval. It is a task of answering a question post...
Search engines contains large amount of information so it is difficult to predict the correct answer...
In this paper, we describe a way to access Arabic Web Question Answering (QA) corpus using a chatbot...
Question answering (QA) task intends to answer questions posed by humans in natural language. Howeve...
In Question answering (QA) system retrieves the precise information from large documents according t...
The authors would like to thank Şeniz Demir for providing the Turkish Wikipedia dataset, Emrah Budur...
International audienceThe field of Question Answering (QA) is very multi-disciplinary as it requires...
The field of Question Answering (QA) is very multidisciplinary as it requires expertise from a large...
Research on Arabic Natural Language Processing is facing a lot of problems due to language complexit...
The general goal of semantic question answering systems is to provide correct answers to natural lan...
In the QA and information retrieval domains progress has been assessed via evaluation campaigns(Clef...
In this paper we report on the progress we have made in developing a unified framework for automatic...
This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in t...
Question Answering QA system is a combination of Information Retrieval IR and Natural Language Pr...
AbstractQuestion answering systems (QASs) generate answers of questions asked in natural languages. ...
Question answering is a subfield of information retrieval. It is a task of answering a question post...
Search engines contains large amount of information so it is difficult to predict the correct answer...
In this paper, we describe a way to access Arabic Web Question Answering (QA) corpus using a chatbot...
Question answering (QA) task intends to answer questions posed by humans in natural language. Howeve...
In Question answering (QA) system retrieves the precise information from large documents according t...
The authors would like to thank Şeniz Demir for providing the Turkish Wikipedia dataset, Emrah Budur...
International audienceThe field of Question Answering (QA) is very multi-disciplinary as it requires...
The field of Question Answering (QA) is very multidisciplinary as it requires expertise from a large...
Research on Arabic Natural Language Processing is facing a lot of problems due to language complexit...
The general goal of semantic question answering systems is to provide correct answers to natural lan...
In the QA and information retrieval domains progress has been assessed via evaluation campaigns(Clef...
In this paper we report on the progress we have made in developing a unified framework for automatic...
This paper presents the QALL-ME benchmark, a multilingual resource of annotated spoken requests in t...
Question Answering QA system is a combination of Information Retrieval IR and Natural Language Pr...
AbstractQuestion answering systems (QASs) generate answers of questions asked in natural languages. ...
Question answering is a subfield of information retrieval. It is a task of answering a question post...
Search engines contains large amount of information so it is difficult to predict the correct answer...
In this paper, we describe a way to access Arabic Web Question Answering (QA) corpus using a chatbot...