Semantic relations between concepts or entities exist in textual documents, keywords or key
phrases, and tags generated in social tagging systems. Relation extraction refers to the
identification and assignment of relations between concepts or entities. Basically, it can explore relations that are implicit to underlying data and then add new knowledge to the different domains.
The purpose of our work was to develop a semi-unsupervised system that was able to automatically extract semantical relations between nominals in a dump extracted from the ialian Wikipedia in November 2008. In addition, we wanted it to correctly classify semantical relations between nominals.
We used a seed-based, pattern-based, semi-unsupervised approach for Relation extraction, while we implemented a variation of Vector Space Model for relation classification. we used manually selected seeds for both purposes. in addition, we implemented a script for the automatic extraction of seed pair to be used with our algorithm
