Shallow Semantics for Relation Extraction
Abstract
This paper presents a new method for extracting meaningful relations from unstructured natural language sources. The method is based on information made available by shallow semantic parsers. Semantic information was used (1) to enhance a dependency tree kernel; and (2) to build semantic dependency structures used for enhanced relation extraction for several semantic classifiers. In our experiments the quality of the extracted relations surpassed the results of kernel-based models employing only semantic class information.
Cite
Text
Harabagiu et al. "Shallow Semantics for Relation Extraction." International Joint Conference on Artificial Intelligence, 2005.Markdown
[Harabagiu et al. "Shallow Semantics for Relation Extraction." International Joint Conference on Artificial Intelligence, 2005.](https://mlanthology.org/ijcai/2005/harabagiu2005ijcai-shallow/)BibTeX
@inproceedings{harabagiu2005ijcai-shallow,
title = {{Shallow Semantics for Relation Extraction}},
author = {Harabagiu, Sanda M. and Bejan, Cosmin Adrian and Morarescu, Paul},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2005},
pages = {1061-1066},
url = {https://mlanthology.org/ijcai/2005/harabagiu2005ijcai-shallow/}
}