TITLE: Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structure 

ABSTRACT: Research into the area of multiparty dialog has grown considerably over
recent years. We present the Molweni dataset, a machine reading comprehension
(MRC) dataset with discourse structure built over multiparty dialog. Molweni's
source samples from the Ubuntu Chat Corpus, including 10,000 dialogs comprising
88,303 utterances. We annotate 30,066 questions on this corpus, including both
answerable and unanswerable questions. Molweni also uniquely contributes
discourse dependency annotations in a modified Segmented Discourse
Representation Theory (SDRT; Asher et al., 2016) style for all of its
multiparty dialogs, contributing large-scale (78,245 annotated discourse
relations) data to bear on the task of multiparty dialog discourse parsing. Our
experiments show that Molweni is a challenging dataset for current MRC models:
BERT-wwm, a current, strong SQuAD 2.0 performer, achieves only 67.7% F1 on
Molweni's questions, a 20+% significant drop as compared against its SQuAD 2.0
performance.
Research into the area of multiparty dialog has grown considerably over
recent years. We present the Molweni dataset, a machine reading comprehension
(MRC) dataset with discourse structure built over multiparty dialog. Molweni's
source samples from the Ubuntu Chat Corpus, including 10,000 dialogs comprising
88,303 utterances. We annotate 30,066 questions on this corpus, including both
answerable and unanswerable questions. Molweni also uniquely contributes
discourse dependency annotations in a modified Segmented Discourse
Representation Theory (SDRT; Asher et al., 2016) style for all of its
multiparty dialogs, contributing large-scale (78,245 annotated discourse
relations) data to bear on the task of multiparty dialog discourse parsing. Our
experiments show that Molweni is a challenging dataset for current MRC models:
BERT-wwm, a current, strong SQuAD 2.0 performer, achieves only 67.7% F1 on
Molweni's questions, a 20+% significant drop as compared against its SQuAD 2.0
performance.
Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structure
http://arxiv.org/abs/2004.05080v3