@inproceedings{koupaee-etal-2023-modeling,
title = "Modeling Complex Event Scenarios via Simple Entity-focused Questions",
author = "Koupaee, Mahnaz and
Durrett, Greg and
Chambers, Nathanael and
Balasubramanian, Niranjan",
editor = "Vlachos, Andreas and
Augenstein, Isabelle",
booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.eacl-main.181",
doi = "10.18653/v1/2023.eacl-main.181",
pages = "2468--2483",
abstract = "Event scenarios are often complex and involve multiple event sequences connected through different entity participants. Exploring such complex scenarios requires an ability to branch through different sequences, something that is difficult to achieve with standard event language modeling. To address this, we propose a question-guided generation framework that models events in complex scenarios as answers to questions about participants. At any step in the generation process, the framework uses the previously-generated events as context, but generates the next event as an answer to one of three questions: what else a participant did, what else happened to a participant, or what else happened. The participants and the questions themselves can be sampled or be provided as input from a user, allowing for controllable exploration. Our empirical evaluation shows that this question-guided generation provides better coverage of participants, diverse events within a domain, comparable perplexities for modeling event sequences, and more effective control for interactive schema generation.",
}
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<abstract>Event scenarios are often complex and involve multiple event sequences connected through different entity participants. Exploring such complex scenarios requires an ability to branch through different sequences, something that is difficult to achieve with standard event language modeling. To address this, we propose a question-guided generation framework that models events in complex scenarios as answers to questions about participants. At any step in the generation process, the framework uses the previously-generated events as context, but generates the next event as an answer to one of three questions: what else a participant did, what else happened to a participant, or what else happened. The participants and the questions themselves can be sampled or be provided as input from a user, allowing for controllable exploration. Our empirical evaluation shows that this question-guided generation provides better coverage of participants, diverse events within a domain, comparable perplexities for modeling event sequences, and more effective control for interactive schema generation.</abstract>
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%0 Conference Proceedings
%T Modeling Complex Event Scenarios via Simple Entity-focused Questions
%A Koupaee, Mahnaz
%A Durrett, Greg
%A Chambers, Nathanael
%A Balasubramanian, Niranjan
%Y Vlachos, Andreas
%Y Augenstein, Isabelle
%S Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
%D 2023
%8 May
%I Association for Computational Linguistics
%C Dubrovnik, Croatia
%F koupaee-etal-2023-modeling
%X Event scenarios are often complex and involve multiple event sequences connected through different entity participants. Exploring such complex scenarios requires an ability to branch through different sequences, something that is difficult to achieve with standard event language modeling. To address this, we propose a question-guided generation framework that models events in complex scenarios as answers to questions about participants. At any step in the generation process, the framework uses the previously-generated events as context, but generates the next event as an answer to one of three questions: what else a participant did, what else happened to a participant, or what else happened. The participants and the questions themselves can be sampled or be provided as input from a user, allowing for controllable exploration. Our empirical evaluation shows that this question-guided generation provides better coverage of participants, diverse events within a domain, comparable perplexities for modeling event sequences, and more effective control for interactive schema generation.
%R 10.18653/v1/2023.eacl-main.181
%U https://aclanthology.org/2023.eacl-main.181
%U https://doi.org/10.18653/v1/2023.eacl-main.181
%P 2468-2483
Markdown (Informal)
[Modeling Complex Event Scenarios via Simple Entity-focused Questions](https://aclanthology.org/2023.eacl-main.181) (Koupaee et al., EACL 2023)
ACL
- Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, and Niranjan Balasubramanian. 2023. Modeling Complex Event Scenarios via Simple Entity-focused Questions. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, pages 2468–2483, Dubrovnik, Croatia. Association for Computational Linguistics.