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This paper describes two experiments: one exploring the amount of information relevant to sense disambiguation contained in the part-of-speech field of entries in a Machine Readable Dictionary (MRD); the other, more practical, experiment attempts sense disambiguation of all content words in a text assigning MRD homographs as sense tags using only part-of-speech information. We have implemented a simple sense tagger which successfully tags 94% of words using this method. A plan to extend this work and implement an improved sense tagger is included.