@inproceedings{li-etal-1999-use,
title = "The use of abstracted knowledge from an automatically sense-tagged corpus for lexical transfer ambiguity resolution",
author = "Li, Hui-Feng and
Moon, Namwon Heo. Kyounghi and
Lee, Jong-Hyeok",
booktitle = "Proceedings of Machine Translation Summit VII",
month = sep # " 13-17",
year = "1999",
address = "Singapore, Singapore",
url = "https://aclanthology.org/1999.mtsummit-1.57",
pages = "390--396",
abstract = "This paper proposes a method for lexical transfer ambiguity resolution using corpus and conceptual information. Previous researches have restricted the use of linguistic knowledge to the lexical level. Since the extracted knowledge is stored in words themselves, these methods require a large amount of space with a low recall rate. On the contrary, we resolve word sense ambiguity by using concept co-occurrence information extracted from an automatically sense-tagged corpus. In one experiment, it achieved, on average, a precision of 82.4{\%} for nominal words, and 83{\%} for verbal words. Considering that the test corpus is completely irrelevant to the learning corpus, this is a promising result.",
}
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%0 Conference Proceedings
%T The use of abstracted knowledge from an automatically sense-tagged corpus for lexical transfer ambiguity resolution
%A Li, Hui-Feng
%A Moon, Namwon Heo. Kyounghi
%A Lee, Jong-Hyeok
%S Proceedings of Machine Translation Summit VII
%D 1999
%8 sep 13 17
%C Singapore, Singapore
%F li-etal-1999-use
%X This paper proposes a method for lexical transfer ambiguity resolution using corpus and conceptual information. Previous researches have restricted the use of linguistic knowledge to the lexical level. Since the extracted knowledge is stored in words themselves, these methods require a large amount of space with a low recall rate. On the contrary, we resolve word sense ambiguity by using concept co-occurrence information extracted from an automatically sense-tagged corpus. In one experiment, it achieved, on average, a precision of 82.4% for nominal words, and 83% for verbal words. Considering that the test corpus is completely irrelevant to the learning corpus, this is a promising result.
%U https://aclanthology.org/1999.mtsummit-1.57
%P 390-396
Markdown (Informal)
[The use of abstracted knowledge from an automatically sense-tagged corpus for lexical transfer ambiguity resolution](https://aclanthology.org/1999.mtsummit-1.57) (Li et al., MTSummit 1999)
ACL