A PROPOSED MODEL FOR AUTOMATIC TEXTUAL DISAMBIGUATION
salwa hamada
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Abstract
The paper is an attempt to utilize the componential analysis theory, the distinctive feature matrices and the conceptual frames as tools for representing human knowledge. It also presents an automatic disambiguation system (ADS) that accounts for textual ambiguities at all the linguistic levels. The traditional methods of tackling ambiguity are not adequate since they specify a few constrains assisted by clues derived from the textual information. The proposed ADS makes extensive use of the linguistic constrains LC's in the disambiguation process (DP). It also utilizes the statistical guide which is, in essence, a combination of the traditional method and the recent statistical methods. It has been found out that this intermarriage between the old (ruled base) and the new (statistical) can help solving a lot of textual analysis problems such as those related to error detection and knowledge inference. Furthermore, the model can serve other linguistic applications such as translation.
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