Entity Resolution and Location Disambiguation in the Ancient Hindu Temples Domain using Web Data

Ayush Maheshwari, Vishwajeet Kumar, Ganesh Ramakrishnan, J. Saketha Nath

Abstract
We present a system for resolving entities and disambiguating locations based on publicly available web data in the domain of ancient Hindu Temples. Scarce, unstructured information poses a challenge to Entity Resolution(ER) and snippet ranking. Additionally, because the same set of entities may be associated with multiple locations, Location Disambiguation(LD) is a problem. The mentions and descriptions of temples exist in the order of hundreds of thousands, with such data generated by various users in various forms such as text (Wikipedia pages), videos (YouTube videos), blogs, etc. We demonstrate an integrated approach using a combination of grammar rules for parsing and unsupervised (clustering) algorithms to resolve entity and locations with high confidence. A demo of our system is accessible at tinyurl.com/templedemos. Our system is open source and available on GitHub.
Anthology ID:
N18-5010
Volume:
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Month:
June
Year:
2018
Address:
New Orleans, Louisiana
Editors:
Yang Liu, Tim Paek, Manasi Patwardhan
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
46–50
Language:
URL:
https://aclanthology.org/N18-5010
DOI:
10.18653/v1/N18-5010
Bibkey:
Cite (ACL):
Ayush Maheshwari, Vishwajeet Kumar, Ganesh Ramakrishnan, and J. Saketha Nath. 2018. Entity Resolution and Location Disambiguation in the Ancient Hindu Temples Domain using Web Data. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pages 46–50, New Orleans, Louisiana. Association for Computational Linguistics.
Cite (Informal):
Entity Resolution and Location Disambiguation in the Ancient Hindu Temples Domain using Web Data (Maheshwari et al., NAACL 2018)
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