Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs

Eun-kyung Kim, Kijong Han, Jiho Kim, Key-Sun Choi


Abstract
This demo deals with the problem of capturing omitted arguments in relation extraction given a proper knowledge base for entities of interest. This paper introduces the concept of a salient entity and use this information to deduce omitted entities in the paragraph which allows improving the relation extraction quality. The main idea to compute salient entities is to construct a graph on the given information (by identifying the entities but without parsing it), rank it with standard graph measures and embed it in the context of the sentences.
Anthology ID:
C18-2011
Volume:
Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations
Month:
August
Year:
2018
Address:
Santa Fe, New Mexico
Editor:
Dongyan Zhao
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
48–52
Language:
URL:
https://aclanthology.org/C18-2011
DOI:
Bibkey:
Cite (ACL):
Eun-kyung Kim, Kijong Han, Jiho Kim, and Key-Sun Choi. 2018. Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs. In Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations, pages 48–52, Santa Fe, New Mexico. Association for Computational Linguistics.
Cite (Informal):
Utilizing Graph Measure to Deduce Omitted Entities in Paragraphs (Kim et al., COLING 2018)
Copy Citation:
PDF:
https://aclanthology.org/C18-2011.pdf