  This paper presents a mechanism of resolving unidentified lexical units in
Text-based Machine Translation (TBMT). In a Machine Translation (MT) system it
is unlikely to have a complete lexicon and hence there is intense need of a new
mechanism to handle the problem of unidentified words. These unknown words
could be abbreviations, names, acronyms and newly introduced terms. We have
proposed an algorithm for the resolution of the unidentified words. This
algorithm takes discourse unit (primitive discourse) as a unit of analysis and
provides real time updates to the lexicon. We have manually applied the
algorithm to news paper fragments. Along with anaphora and cataphora
resolution, many unknown words especially names and abbreviations were updated
to the lexicon.
