Abstract
The process of knowledge acquisition can be viewed as a question-answer game between a student and a teacher in which the student typically starts by asking broad, open-ended questions before drilling down into specifics (Hintikka, 1981; Hakkarainen and Sintonen, 2002). This pedagogical perspective motivates a new way of representing documents. In this paper, we present SQUASH (Specificity-controlled Question-Answer Hierarchies), a novel and challenging text generation task that converts an input document into a hierarchy of question-answer pairs. Users can click on high-level questions (e.g., “Why did Frodo leave the Fellowship?”) to reveal related but more specific questions (e.g., “Who did Frodo leave with?”). Using a question taxonomy loosely based on Lehnert (1978), we classify questions in existing reading comprehension datasets as either GENERAL or SPECIFIC . We then use these labels as input to a pipelined system centered around a conditional neural language model. We extensively evaluate the quality of the generated QA hierarchies through crowdsourced experiments and report strong empirical results.- Anthology ID:
- P19-1224
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2321–2334
- Language:
- URL:
- https://aclanthology.org/P19-1224
- DOI:
- 10.18653/v1/P19-1224
- Cite (ACL):
- Kalpesh Krishna and Mohit Iyyer. 2019. Generating Question-Answer Hierarchies. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 2321–2334, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Generating Question-Answer Hierarchies (Krishna & Iyyer, ACL 2019)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/P19-1224.pdf
- Code
- additional community code
- Data
- CoQA, QuAC, SQuAD