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
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
48–52
Language:
URL:
https://www.aclweb.org/anthology/C18-2011
DOI:
Bib Export formats:
BibTeX MODS XML EndNote
PDF:
http://aclanthology.lst.uni-saarland.de/C18-2011.pdf