Coarse-grained Semantic Characterization of Large Knowledge Resources

Abstract

This work presents an experimental study about the automatic assignment of semantic groups to concepts of large knowledge resources (KR) such as DBpedia1 or BabelNet2. Our proposal combines a simple lexico-statistical method for hypernym extraction combined with document and word embeddings extracted from Wikipedia. Results are encouraging and open new directions for improving other tasks related to large KR management like debugging and semantic annotation.