Modeling Complex Event Scenarios via Simple Entity-focused Questions
Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan, Balasubramanian

TL;DR
This paper introduces a question-guided generation framework for modeling complex event scenarios by answering participant-focused questions, enabling better coverage, diversity, and controllability in event sequence generation.
Contribution
It proposes a novel question-guided approach that models events as answers to participant-related questions, enhancing exploration and control in complex scenario modeling.
Findings
Improved coverage of participants in generated scenarios
Enhanced diversity of events within a domain
Comparable perplexities to standard event language models
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…
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Taxonomy
TopicsSemantic Web and Ontologies · Topic Modeling · Natural Language Processing Techniques
