Assessing Language Identification over DBpedia

摘要

Multilingual knowledge bases are the key for cross-lingual and multilingual applications such as Question Answering, Machine Translation, and Search. They facilitate information access and provide valuable training corpora for multi- and cross-lingual methods and frameworks. In this work, we evaluate the performance of different language identification methods and frameworks over DBpedia. We show that these approaches perform poorly on rdfs:labels.