DARC-IT: A DAtaset for reading comprehension in Italian

Conference Paper
Publication Date:
2018
abstract:
In this paper, we present DARC-IT, a new reading comprehension dataset for the Italian language aimed at identifying 'question-worthy' sentences, i.e. sentences in a text which contain information that is worth asking a question about. The purpose of the corpus is twofold: to investigate the linguistic profile of question-worthy sentences and to support the development of automatic question generation systems.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Reading Comprehension
List of contributors:
Authors of the University:
Handle:
https://iris.cnr.it/handle/20.500.14243/392547
Published in:
CEUR WORKSHOP PROCEEDINGS
Series