Abstract
One strategy for facilitating reading comprehension is to present information in a question-and-answer format. We demo a system that integrates the tasks of question answering (QA) and question generation (QG) in order to produce Q&A items that convey the content of multi-paragraph documents. We report some experiments for QA and QG that yield improvements on both tasks, and assess how they interact to produce a list of Q&A items for a text. The demo is accessible at qna.sdl.com.- Anthology ID:
- 2021.eacl-demos.6
- Volume:
- Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
- Month:
- April
- Year:
- 2021
- Address:
- Online
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 40–52
- Language:
- URL:
- https://aclanthology.org/2021.eacl-demos.6
- DOI:
- 10.18653/v1/2021.eacl-demos.6
- Cite (ACL):
- Melissa Roemmele, Deep Sidhpura, Steve DeNeefe, and Ling Tsou. 2021. AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 40–52, Online. Association for Computational Linguistics.
- Cite (Informal):
- AnswerQuest: A System for Generating Question-Answer Items from Multi-Paragraph Documents (Roemmele et al., EACL 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.eacl-demos.6.pdf
- Code
- roemmele/answerquest
- Data
- 100DOH