Semantic Inference in Natural Language: Validating a Tractable Approach
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Natural Language. Pages 1346-1352.
Abstract
This paper is concerned with an inferential approach to information extraction, reporting in particular on the results of an empirical study that was performed to validate the approach. The study brings together two lines of research: (I) the RHO framework for tractable terminological knowledge representation, and (2) the Alembic message understanding system. There are correspondingly two principal aspects of interest to this work. From the knowledge representation perspective, the present study serves to validate experimentally a normal form hypothesis that guarantees tractability of inference in the RHO framework. From the message processing perspective, this study substantiates the utility of limited inference to information extraction.
@inproceedings{ijcai1995p173,
title = {Semantic Inference in Natural Language: Validating a Tractable Approach},
author = {Vilain, Marc B.},
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 = {1346--1352},
year = {1995},
note = {Natural Language},
url = {https://ijcai.org/proceedings/1995/173},
}
TY - CPAPER TI - Semantic Inference in Natural Language: Validating a Tractable Approach AU - Vilain, Marc B. T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 1346 EP - 1352 UR - https://ijcai.org/proceedings/1995/173 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
