The Knowledge Required to Interpret Noun Compounds
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 1483-1484.
Abstract
Noun compound interpretation is the task of determining the semantic relations among the constituents of a noun compound. For example, "concrete floor" means a floor made of concrete, while "gymnasium floor" is the floor region of a gymnasium. We would like to enable knowledge acquisition systems to interpret noun compounds, as part of their overall task of translating imprecise and incomplete information into formal representations that support automated reasoning. However, if interpreting noun compounds requires detailed knowledge of the constituent nouns, then it may not be worth doing: the cost of acquiring this knowledge may outweigh the potential benefit. This paper describes an empirical investigation of the knowledge required to interpret noun compounds. It concludes that the axioms and ontological distinctions important for this task are derived from the top levels of a hierarchical knowledge base (KB); detailed knowledge of specific nouns is less important. This is good news, not only for our work on knowledge acquisition systems, but also for research on text understanding, where noun compound interpretation has a long history. A more detailed version of this paper can be found in [Fan eta /.,2003].
@inproceedings{ijcai2003p244,
title = {The Knowledge Required to Interpret Noun Compounds},
author = {Fan, James and Barker, Ken and Porter, Bruce W.},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {1483--1484},
year = {2003},
url = {https://ijcai.org/proceedings/2003/244},
}
TY - CPAPER TI - The Knowledge Required to Interpret Noun Compounds AU - Fan, James AU - Barker, Ken AU - Porter, Bruce W. T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 1483 EP - 1484 UR - https://ijcai.org/proceedings/2003/244 ER -Copied
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