Analysis done on the nature of the data posted on the WWW (World Wide Web) reveal that more than 80% of the data over the WWW is in unstructured text format. Hence extracting information from text is of paramount importance both for academic and business purposes. Simultaneously, evolution of web technology led to the novel concept of Semantic Web, which is an extension of the current web in which information is given well-defined meaning, enabling computers and people to work in cooperation in a better way. Integration of voluminous, legacy text data that are unstructured and semi-structured, into Semantic Web format is a challenging and daunting task for the research community. This paper is an attempt to marry the concept of Semantic Web format with unstructured text, thus to enable the computers to discover the previously unknown information, by automatically extracting information from different written resources.
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