Example-Based Word-Sense Disambiguation

Naohiko URAMOTO

Example-Based Word-Sense Disambiguation

Naohiko URAMOTO

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This paper presents a new method for resolving lexical (word sense) ambiguities inherent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an example-base, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.

Publication: IEICE TRANSACTIONS on Information Vol.E77-D No.2 pp.240-246

Publication Date: 1994/02/25

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Type of Manuscript: Special Section PAPER (Special Issue on Natural Language Processing and Understanding)

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Naohiko URAMOTO, "Example-Based Word-Sense Disambiguation" in IEICE TRANSACTIONS on Information, vol. E77-D, no. 2, pp. 240-246, February 1994, doi: .
Abstract: This paper presents a new method for resolving lexical (word sense) ambiguities inherent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an example-base, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.
URL: https://global.ieice.org/en_transactions/information/10.1587/e77-d_2_240/_p

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@ARTICLE{e77-d_2_240,
author={Naohiko URAMOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Example-Based Word-Sense Disambiguation},
year={1994},
volume={E77-D},
number={2},
pages={240-246},
abstract={This paper presents a new method for resolving lexical (word sense) ambiguities inherent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an example-base, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.},
keywords={},
doi={},
ISSN={},
month={February},}

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TY - JOUR
TI - Example-Based Word-Sense Disambiguation
T2 - IEICE TRANSACTIONS on Information
SP - 240
EP - 246
AU - Naohiko URAMOTO
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E77-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 1994
AB - This paper presents a new method for resolving lexical (word sense) ambiguities inherent in natural language sentences. The Sentence Analyzer (SENA) was developed to resolve such ambiguities by using constraints and example-based preferences. The ambiguities are packed into a single dependency structure, and grammatical and lexical constraints are applied to it in order to reduce the degree of ambiguity. The application of constraints is realized by a very effective constraint-satisfaction technique. Remaining ambiguities are resolved by the use of preferences calculated from an example-base, which is a set of fully parsed word-to-word dependencies acquired semi-automatically from on-line dictionaries.
ER -