TY - GEN
T1 - Asking It All
T2 - 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021
AU - Pyatkin, Valentina
AU - Roit, Paul
AU - Michael, Julian
AU - Tsarfaty, Reut
AU - Goldberg, Yoav
AU - Dagan, Ido
N1 - Publisher Copyright: © 2021 Association for Computational Linguistics
PY - 2021/1/1
Y1 - 2021/1/1
N2 - Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention and a passage, requires producing a set of questions asking about all possible semantic roles of the predicate. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage. Unlike most existing approaches to question generation, our approach does not require conditioning on existing answers in the text. Instead, we condition on the type of information to inquire about, regardless of whether the answer appears explicitly in the text, could be inferred from it, or should be sought elsewhere. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage ontology of predicates and roles.
AB - Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention and a passage, requires producing a set of questions asking about all possible semantic roles of the predicate. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage. Unlike most existing approaches to question generation, our approach does not require conditioning on existing answers in the text. Instead, we condition on the type of information to inquire about, regardless of whether the answer appears explicitly in the text, could be inferred from it, or should be sought elsewhere. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage ontology of predicates and roles.
UR - http://www.scopus.com/inward/record.url?scp=85127026975&partnerID=8YFLogxK
U2 - 10.18653/v1/2021.emnlp-main.108
DO - 10.18653/v1/2021.emnlp-main.108
M3 - منشور من مؤتمر
T3 - EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings
SP - 1429
EP - 1441
BT - EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings
PB - Association for Computational Linguistics (ACL)
Y2 - 7 November 2021 through 11 November 2021
ER -