Lexicon Acquisition: Learning from Corpus by Capitalizing on Lexical Categories
Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. Speech and Natural Language. Pages 1556-1563.
Abstract
Text examples must be exploited in the acquisition of lexical structures. However, neither syntactic nor semantic features are provided by the text itself, and so acquisition must be aided by additional resources. We investigate the application of an existing resource, a set of lexical categories, as a prediction method. We present an algorithm that applies (a) top-down prediction based on lexical categories; (b) bottom-up validation by scanning text examples. Finally, we discuss the issue of semantic bootstrapping and identify its theoretical and practical limitations.
@inproceedings{ijcai1989p248,
title = {Lexicon Acquisition: Learning from Corpus by Capitalizing on Lexical Categories},
author = {Zernik, Uri},
booktitle = {Proceedings of the Eleventh International Joint Conference on
Artificial Intelligence, {IJCAI-89}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {N. S. Sridharan},
pages = {1556--1563},
year = {1989},
month = {8},
note = {Speech and Natural Language},
url = {https://ijcai.org/proceedings/1989/248},
}
TY - CPAPER TI - Lexicon Acquisition: Learning from Corpus by Capitalizing on Lexical Categories AU - Zernik, Uri T2 - Proceedings of the Eleventh International Joint Conference on Artificial Intelligence, IJCAI-89 PB - International Joint Conferences on Artificial Intelligence PY - 1989 SP - 1556 EP - 1563 UR - https://ijcai.org/proceedings/1989/248 ER -Copied
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