Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model
Sathish Reddy, Dinesh Raghu, Mitesh M. Khapra, Sachindra Joshi
Abstract
In recent years, knowledge graphs such as Freebase that capture facts about entities and relationships between them have been used actively for answering factoid questions. In this paper, we explore the problem of automatically generating question answer pairs from a given knowledge graph. The generated question answer (QA) pairs can be used in several downstream applications. For example, they could be used for training better QA systems. To generate such QA pairs, we first extract a set of keywords from entities and relationships expressed in a triple stored in the knowledge graph. From each such set, we use a subset of keywords to generate a natural language question that has a unique answer. We treat this subset of keywords as a sequence and propose a sequence to sequence model using RNN to generate a natural language question from it. Our RNN based model generates QA pairs with an accuracy of 33.61 percent and performs 110.47 percent (relative) better than a state-of-the-art template based method for generating natural language question from keywords. We also do an extrinsic evaluation by using the generated QA pairs to train a QA system and observe that the F1-score of the QA system improves by 5.5 percent (relative) when using automatically generated QA pairs in addition to manually generated QA pairs available for training.- Anthology ID:
- E17-1036
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 376–385
- Language:
- URL:
- https://aclanthology.org/E17-1036
- DOI:
- Cite (ACL):
- Sathish Reddy, Dinesh Raghu, Mitesh M. Khapra, and Sachindra Joshi. 2017. Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers, pages 376–385, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Generating Natural Language Question-Answer Pairs from a Knowledge Graph Using a RNN Based Question Generation Model (Reddy et al., EACL 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/E17-1036.pdf
- Data
- SimpleQuestions