Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings

Jaydeep Sen, Tanaya Babtiwale, Kanishk Saxena, Yash Butala, Sumit Bhatia, Karthik Sankaranarayanan


Abstract
Natural Language Query interfaces allow the end-users to access the desired information without the need to know any specialized query language, data storage, or schema details. Even with the recent advances in NLP research space, the state-of-the-art QA systems fall short of understanding implicit intents of real-world Business Intelligence (BI) queries in enterprise systems, since Natural Language Understanding still remains an AI-hard problem. We posit that deploying ontology reasoning over domain semantics can help in achieving better natural language understanding for QA systems. In this paper, we specifically focus on building a Schema Aware Semantic Reasoning Framework that translates natural language interpretation as a sequence of solvable tasks by an ontology reasoner. We apply our framework on top of an ontology based, state-of-the-art natural language question-answering system ATHENA, and experiment with 4 benchmarks focused on BI queries. Our experimental numbers empirically show that the Schema Aware Semantic Reasoning indeed helps in achieving significantly better results for handling BI queries with an average accuracy improvement of ~30%
Anthology ID:
2020.coling-main.115
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
1334–1345
Language:
URL:
https://aclanthology.org/2020.coling-main.115
DOI:
10.18653/v1/2020.coling-main.115
Bibkey:
Cite (ACL):
Jaydeep Sen, Tanaya Babtiwale, Kanishk Saxena, Yash Butala, Sumit Bhatia, and Karthik Sankaranarayanan. 2020. Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings. In Proceedings of the 28th International Conference on Computational Linguistics, pages 1334–1345, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Schema Aware Semantic Reasoning for Interpreting Natural Language Queries in Enterprise Settings (Sen et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.115.pdf