A Dependency-based Method for Evaluating Broad-Coverage Parsers
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Natural Language. Pages 1420-1426.
Abstract
With the emergence of broad-coverage parsers, quantitative evaluation of parsers becomes increasingly more important. We propose a dependency-based method for evaluating broad-coverage parsers. The method offers several advantages over previous methods that are based on phrase boundaries. The error count score we propose here is not only more intuitively meaningful than other scores, but also more relevant to semantic interpretation. We will also present an algorithm for transforming constituency trees into dependency trees so that the evaluation method is applicable to both dependency and constituency grammars . Finally, we discuss a set of operations for modifying dependency trees that can be used to eliminate inconsequential differences among different parse trees and allow us to selectively evalu ate different aspects of a parser.
@inproceedings{ijcai1995p183,
title = {A Dependency-based Method for Evaluating Broad-Coverage Parsers},
author = {Lin, Dekang},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {1420--1426},
year = {1995},
note = {Natural Language},
url = {https://ijcai.org/proceedings/1995/183},
}
TY - CPAPER TI - A Dependency-based Method for Evaluating Broad-Coverage Parsers AU - Lin, Dekang T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 1420 EP - 1426 UR - https://ijcai.org/proceedings/1995/183 ER -Copied
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